STEM Research Projects

Recent research has developed algorithms for identifying such bots through measures of coordination: accounts that post to social media at similar times, or with similar, recognisable patterns of behaviour. Such coordination is hypothesised to create social influence and may be used in grey zone conflict. The project will develop novel methods for measuring, mapping and modelling the online social spread of misinformation using the full extent of information (e.g., network structure and full post content) available.

Project available for: Mphil and PhD students

a) the ability to detect when their machine learning models no longer fit the deployment conditions.
b) to initiate self-supervised learning using data sampled from the endless stream of information captured by the robot's sensors during operation.

This PhD will address the above two points and develop novel self-supervised active robot learning algorithms.

Project available for: PhD students

This spectral band is in the last underutilised part of the electromagnetic spectrum for sensing, imaging, and communications purposes. The terahertz waves are capable of penetrating dry, nonmetallic materials with sub-millimetre spatial and depth resolutions. This property makes it ideal for noncontact security screening of humans and objects and non-destructive evaluation of a variety of materials. The generous bandwidth is promising for high-speed line-of-sight wireless communications. In the Terahertz Engineering Laboratory, we have a vast array of research activities spanning terahertz metasurfaces, unconventional antennas, highly efficient integrated platform, non-destructive evaluation of targets, stand-off radar, and 6G communications.

Project available for: Mphil and PhD students

The inner surface of these platforms will be functionalized with a model organic fluorophore via micellar solubilization of a surfactant. The resultant organic–inorganic composite structures will provide model platforms to develop optically pumped solid-state random lasers with well-resolved, intense lasing bands. The effect of NAA’s geometric features on the random lasing characteristics of these model platforms will be elucidated by precisely engineering its nanopore diameter, nanopore length, interpore distance, and ordering. Random lasers based on NAA will provide new opportunities to engineer cost-competitive, highly controllable, and integrable light sources for a broad range of photonic technologies such as sensing, hyperspectral imaging, high-resolution spectroscopic analysis, and photonic circuits.

Project available for: Mphil and PhD students

It requires a strong background in third-year undergraduate pure mathematics and provides an introduction at the MPhil level to advanced complex analysis and complex geometry, paving the way to a PhD in this area.

Project available for: Mphil students

The projects fit into a rich context of contemporary research on complex manifolds that have a very large group of automorphisms or a very large monoid of endomorphisms.  A strong background in pure mathematics at the honours or master’s level is necessary.

Project available for: PhD students

The successful candidate must commence study by 30 June 2023 and will be working within a multidisciplinary team funded by an Australian Research Council grant awarded to Dr Tatiana Soares da Costa and Prof Marilyn Anderson, including a postdoctoral researcher.

Herbicide resistance represents one of the greatest threats to global food security and given that our current herbicides have begun to fail, novel approaches are urgently required to develop new treatments. This project aims to tackle herbicide resistance by identifying new herbicide candidates that inhibit amino acid biosynthesis. Specifically, we will exploit the similarity between bacterial and plant enzymes in these pathways to re-purpose failed 'antibiotics'. The expected outcomes of this exciting project include advances in our knowledge of the structure, function and inhibition of novel herbicide targets, the identification of compounds with herbicidal activity, and significant long-term contributions towards food security. The multidisciplinary PhD project will integrate innovative approaches in biochemistry, molecular biology and plant biology.

The successful candidate will be an integral part of the team of researchers involved in this project and will be expected to collaborate closely with colleagues at the University of Adelaide.

Project available for: PhD students

However, changes in their communities and populations caused by climate change and/or host population decline have the potential to impact host health and disrupt global ecosystems. Our understanding of how climate change and host declines affect parasites and pathogens is poor, and lacks a long-term perspective. This project looks to use DNA preserved within ancient dung from different vertebrate species to reconstruct how parasite/pathogen populations and communities responded to actual climate change and host decline events in the past. These unique ‘real-time’ insights into long-term processes will help answer pivotal questions in parasite/pathogen ecology and revolutionise our understanding of extinction risks within parasites.

Project available for: PhD students

Sedimentary DNA can be used to reconstruct past plant and animal communities, even in the absence of visible remains such as seeds or bones. Moreover, DNA from sediments can provide population-level insights into particular species of interest. While now widely applied in the Northern Hemisphere, sedimentary ancient DNA research is still in its infancy and has had limited investigation in the Southern Hemisphere. This project will look to develop this tool through exploring the preservation and potential applications of DNA from Australian cave sediments spanning the past 50,000 years.

Project available for: PhD students

Using electro-acoustic coupling in semiconductors, we expect to reduce optical power requirements hundredfold, enabling the emergence of practically deployable processors using ordinary telecom lasers. The expected project outcomes are inexpensive, compact, stable and energy efficient microwave photonic processors, a key requirement for reference standards and precision measurements of time and frequency.

Project available for: PhD students

These nonlinear photonic integrated circuits will provide a path for the generation of optical frequency combs from the ultraviolet all the way to the near-infrared.

Project available for: PhD students

This project will develop innovative packaging materials from biodegradable sources. Novel technologies will be incorporated into packaging materials (e.g. coatings, sensors) which aim to create "smart, functional" packaging materials which are attractive to consumers, helpful for food suppliers, and valued by packaging manufacturers.

Project available for: PhD students

Plasma discharges are an emerging technology in agriculture and food research. This project is aimed at understanding how low-temperature plasmas can be used as an innovative food or seed treatment. Research outcomes aim to benefit food processing, food production, horticulture, and ecology.

Project available for: PhD students

This project will develop antimicrobial surface coatings to prevent hospital acquired infections related to surfaces and devices. A novel aspect of this research is to understand cell-surface interactions and how this influences antibiotic mechanism of action. Finding novel drug mechanisms is one strategy that could help to overcome antimicrobial resistance.

Project available for: PhD students

Salmonella is a major foodborne pathogen and its virulence could be affected by the storage temperature. This project hypothesizes that the storage of eggs at room temperature can lead to an increase in Salmonella virulence. The project involves working with human health departments, egg industry and food regulators.

Project available for: Mphil and PhD students

Avian hepatitis can cause a big liver and spleen disease and can reduce a bird's immune response. Infection can cause a drop in egg production and increase the risk of other bacterial infections such as spotty liver disease. The project involved working closely with the industry and developing the first vaccine in Australia.

Project available for: Mphil and PhD students

The University of Adelaide and the South Australian Research and Development Institute (SARDI) were recently awarded a multi-million dollar grant from the Commonwealth government to restore large areas of seagrass north of Adelaide; a project that will build on the wealth of experience in seagrass restoration that SARDI has developed over recent years.

This PhD project aims to measure and value the myriad benefits of seagrass restoration to nature and people by conducting environmental and economic accounting of Adelaide’s seagrass restoration projects. The student will have the opportunity to participate in the seagrass restoration project deployments and use them, as well as nearby control areas, as the basis for their research.

Potential areas of study could include:
1. Assessing the intrinsic value of seagrass restoration to people.
2. Assessing the ‘blue carbon’ sequestration gains from seagrass restoration projects.
3. Determining and valuing the biological resource benefits (e.g. changes in numbers of fish and invertebrates) and seascape connectivity benefits of seagrass restoration.
4. Understanding the benefits of intact seagrass meadows for stabilising sediments and protecting shorelines, and the value of this service for climate change adaption.

We are particularly interested in students with experience in or understanding of environmental economics and/or social science, although a project purely focussed on ecology would also be possible. The project would be undertaken in conjunction with economics and social science researchers. There is scope for multiple PhD projects associated with this large-scale seagrass restoration project, so please get in touch if you would like to discuss the opportunity.

Project available for: PhD students

The University of Adelaide and the South Australian Research and Development Institute (SARDI) were recently awarded a multi-million dollar grant from the Commonwealth government to restore large areas of seagrass north of Adelaide; a project that will build on the wealth of experience in seagrass restoration that SARDI have developed over recent years.

This PhD project aims to increase understanding of the early seedling stage of Posidonia and/or Amphibolis seagrass, so as to improve restoration success. The student will participate in the seagrass restoration project deployments and use them to form the basis of their experimental research. Potential areas of study could include:
1. Improving culture techniques in the laboratory so as to be able to undertake experiments to understand the early growth requirements of seagrass seedlings.
2. Determining optimal handling techniques for seagrass fruits collected off the beach, so as to enhance survival of seedlings.
3. Assessing the optimal spatial arrangement for laying out seedlings to enhance restoration success and timelines.

There is scope for multiple PhD projects associated with this large-scale seagrass restoration project, so please get in touch if you would like to discuss the opportunity.

Project available for: PhD students

The main objective of the project is to establish a geotechnical assessment model based on rock properties measured from lab experiments. Such a model will cover linear, nonlinear (e.g., fracturing/caving/failure) and anisotropic behaviours of rocks, the strata movement (including surface subsidence), and the long-term impacts of ISG on surrounding strata to aid environmental assessments. Another objective is to establish a fully coupled geotechnical and gasification model for ISG operations. A Ph.D. student is requested for the project. And the i-PhD project is possible for an eligible student. "

Due to the extreme conditions in ISG (say 500 meters underground and reactions with temperatures up to 1100 Celsius), it is very difficult if not impossible to measure and understand the flow field, temperature field, reactions, and cavity growth in the ISG processes. Therefore, a well-validated model that can simulate the complex physical/chemical phenomenon in the ISG processes is essential for the design and operation of the ISG, and for the subsidence analysis of the ISG site.

The aim of the project is to develop a computational fluid dynamics (CFD) model based on the data obtained from a lab-scale ISG reactor and other coal property measurements and to carry out a series of validation of the model. The validated model can be applied to simulate the ISG processes in the industry to obtain a better understanding of the reactions, flow fields, temperature fields, product gases, and cavity growth in the ISG cavities. These CFD results are essential for the ISG design and operations and will be used for the subsidence analysis. Another objective of the project is to design and build a lab-scale gasification reactor for model development and validation.

A Ph.D. student is requested for the project. And the i-PhD project is possible for an eligible student.

AMR gene mobility occurs through associations with different types of mobile genetic elements (MGEs), including plasmids, phages, transposable elements, and integrons. Research in the Sheppard lab uses whole-genome sequencing of bacterial pathogens to investigate transmission pathways of mobile AMR genes. We use both short and long-read sequencing to obtain complete, closed bacterial genome assemblies, where MGEs associated with AMR genes are fully resolved.

Projects are available spanning a range of topics including: identifying MGEs driving the global dissemination of key AMR genes; characterising the impact of MGE activity on bacterial genome evolution; determining preferential integration sites for transposable elements carrying AMR genes; development of a novel evolutionary framework for tracking horizontal gene transfer; software development for mobile AMR gene tracking. Some bioinformatics experience is preferred, but not required. The projects are also suitable for individuals with a biological background who are keen to apply themselves in a computational setting, as well as individuals with a computational background who are motivated to learn the relevant biology.

Project available for: Mphil and PhD students

But membrane-based technologies are often limited by the inadequate performance of current membranes. Membranes made from 2D materials, such as graphene or hexagonal boron nitride, hold exceptional promise for tackling many of these challenges. But large gaps in knowledge of transport processes in 2D membranes, particularly those driven by concentration gradients, prevents predictive design and optimisation of 2D membranes for applications.

The aim of this project is to develop an unprecedented theoretical understanding of the fluid and membrane parameters that control concentration-gradient-driven transport of liquid mixtures and solutions through 2D membranes and to investigate deviations from continuum hydrodynamics due to molecular effects that can potentially be harnessed for applications.

The project will address these issues using novel non-equilibrium molecular simulation algorithms for concentration-gradient-driven flow that we have developed, along with finite-element continuum hydrodynamics simulations and theory.

Project available for: Mphil and PhD students

One strategy to address this issue to simplify the representation of a molecular system by systematically eliminating unimportant degrees-of-freedom to improve computational efficiency without sacrificing accuracy.

This project will use methods from statistical mechanics, machine learning, and artificial intelligence to develop algorithms to automate the dimensionality reduction process. The project will focus on developing novel methods to ""coarse grain"" the structure and dynamics of highly anisotropic molecules such as organic semiconductors used in novel flexible electronic devices including solar cells, light-emitting diodes, and transistors, for which molecular packing on a wide range of length scales strongly influences device performance.

Project available for: Mphil and PhD students

Persistent organic pollutants (POPs) can cause cancer and birth defects in humans and are destructive to animal and aquatic lifeforms. POPs are by-products of some agricultural and industrial processes and do not degrade naturally due to their strong chemical bonds (e.g. C-Cl, C-F) which are resistant to chemical- and bio-degradation.

The concentration of POPs measured in humans, including in Australia, is increasing with adverse health affects (growth, reproduction) with direct correlation to POP content reported with mounting evidence. There is a need to develop methods and processes for effective degradation of POPs to mitigate their emerging health and environmental effects. Research projects in this field will focus on the synthesis of new photocatalytic materials with designed electronic band structure to break C-Cl or C-F bonds (which are present in all POPs). Materials of interest are titanium and tantalum based perovskites such as SrTiO3 and NaTaO3.

Recent insights in photocatalysis have discovered that significant improvement in photocatalytic efficiency is possible with metal ion doping of semiconductors and this may prove to be critical in the efficient degradation of POPs.

A final aspect of this research is the translation of research to commercial application and photocatalytic processes and reactors will be developed with close ties to industry to degrade pollutants relevant to Australia. This environmental remediation project will develop skills in inorganic synthesis, light initiated reactions, liquid and gas chromatography, electron microscopy, x-ray diffraction and analytical chemistry.

Project available for: Mphil and PhD students

Photocatalytic materials have the potential to breakdown persistent pollutants from the environment. Each new material requires extensive and time-consuming experiments to determine its reaction kinetics for the degradation of a particular pollutant, which then needs to be replicated for any additional pollutants of interest and co-contaminants which may be present in the field.

In order to rapidly assess photocatalytic properties and then aid in the process of material optimisation and future-decision making, this project will develop a self-driving laboratory augmented with artificial intelligence software. This approach will follow Bayesian optimization to direct the reaction sequence to maximise either reaction rate or reaction yield far more efficiently than is possible with a conventional manual approach. Both continuous parameters (flow rate, concentration, light intensity and catalyst loading) and categorical parameters (catalyst composition and pollutant type) will be optimised and will be used to suggest subsequent experiments and drive material design.

This project combines material synthesis and characterisation with computer science (hardware and software) for an environmental remediation application. It will develop skills in inorganic synthesis, light initiated reactions, computer programming and machine learning.

Project available for: Mphil and PhD students

Hydrogen is a portable, renewable and non-polluting fuel source that could replace oil and natural gas. The challenge holding back the wide scale use of hydrogen as a fuel source is the difficulty in its production from water splitting. Electrolysis powered by renewable energy is one possible method but is currently not cost competitive with other hydrogen production methods and has seen only minor improvements in recent years. Photocatalytic water splitting has seen major improvements in recent years with 1000x improvement since 2015 unlocked by optimising photocatalyst and co-catalyst systems.

Our research in this area use the most active photocatalysts available under extreme conditions where photocatalysis has particular advantages over other hydrogen production methods. Examples include photocatalysis from air which may be used to produce fuel in remote locations such as islands or deserts, photocatalysis in extra-terrestrial-like conditions such as on asteroids or the moon, and photocatalysis under sunlight concentrated using reflectors or lenses.

The impetus of this research direction is that the efficiency of photocatalytic hydrogen production has been shown to increase with temperature, light intensity and UV illumination. Analysis of the photocatalysts before and after use, particularly by electron microscopy, will provide insights in improving photocatalysis activity and longevity.

This renewable energy project will develop skills in inorganic synthesis, light initiated reactions, gas chromatography, electron microscopy and chemical engineering.

Project available for: Mphil and PhD students

The project will involve; mapping buried volcanoes using 3D seismic reflection; studying multiphase flow (including CO2) in volcanic rocks; and field work in volcanic provinces to generate virtual outcrop models that will inform reservoir simulation.

Project available for: Mphil and PhD students

The main aims of the project include: determining contemporary, pre-injection stresses, pore pressures and rock strengths; developing 3D structural models for potential CO2 and hydrogen storage sites; reservoir-to-basin scale numerical-geomechanical modelling; and geomechanical risking to evaluate the likelihood of induced seismicity.

Project available for: Mphil and PhD students

The project will involve: detailed mapping of along-slope sediment drifts using high-resolution 3D seismic data from the Great Australian Bight; re-evaluation of Cenozoic strata recovered during IODP/ODP drilling; and integration with palaeoceanographic modelling to evaluate hypothesis for the onset of modern bottom currents.

Project available for: Mphil and PhD students

The Eromanga Basin has undergone a complex history of mantle-related subsidence, uplift and erosion over the last 200 million years. Deciphering the mechanisms responsible for vertical crustal movements across the Eromanga Basin is fundamental to understand the magnitude and timing of mantle-related uplift in a sedimentary basin system that has been identified as a candidate for CO2 storage. This project aims to bring together different datasets (seismic, well, gravity and magnetic) to produce a basin-wide assessment of Cretaceous strata. Geodynamic modelling will be applied (e.g. using the Advanced Solver for Problems in Earth Sciences, ASPECT) to investigate the mechanisms, timing and magnitude of mantle-related uplift across the basin.

Project available for: Mphil and PhD students

The project aims to apply novel laser-based dating of sedimentary rocks, coupled with metal isotope proxy reconstructions of the basin’s palaeogeography, hydrological connectivity and past redox conditions, which are all critical parameters to guide and de-risk future exploration of sediment- hosted resources in this frontier basin. Anticipated outcomes will benefit Australia's resources economy, while providing insights into the evolution of Earth’s surface environment in deep time.

Project available for: PhD students

Starting strains are exposed poor nutritional or alcohol rich environments: those that survive these harsh environments can then be used in subsequent experiments, re-enforcing desirable genetic traits. In this project, we will develop stochastic and deterministic mathematical models of the dynamics of yeast strains bred in these conditions. The aim is to optimise experimental conditions that maximise the evolution of yeast suitable for use in the wine fermentation process. A background in applied mathematics and knowledge of computer programming will be required.

Project available for: Mphil and PhD students

The analysis of experimental images of high-throughput assays plays an important role in assessing the response of microbial growth due to environmental factors and genetic traits. TAMMiCol: Tool for Analysis of the Morphology of Microbial Colonies, can automatically process experimental images into binary data, which can then be analysed with descriptive statistics and machine-learning algorithms to quantify and classify the microbial growth. In this project, you will convert the open source TAMMiCol code (Matlab) into a user-friendly native app for mobile devices (e.g. iPads) to enable the processing of experimental images in the laboratory by biologists who may not be that tech savvy or have little to no experience in using more sophisticated image processing tools.

Project available for: Mphil and PhD students

Both are highly non-uniform spatial-temporal processes, often producing complex spatial patterns. The overall goal of this project is to develop models that predict the time evolution of colony morphology. In this project, you will explore both continuum and discrete approaches to develop a model of the growth process. The data for the statistical analysis and model validation will be obtained from laboratory experiments.

Project available for: Mphil and PhD students

Of particular interest to this project is the potential formation of localised three-dimensional waves, which decay in the far-field away from the topographic forcing. Progress will be made on this by studying solutions to the Kadomtsev-Petviashvili equation. More challenging will be the study of such structures for the fully nonlinear equations, and this will be tackled using boundary integral methods.

Project available for: Mphil and PhD students

This project will tackle this major issue pursuing analysis of the Run3 data (2022-2025) collected with the ATLAS experiment at CERN.

Project available for: Mphil and PhD students

The fluid flow in general occur in complex coupled hydro-thermo-mechanical-chemical (HTMC) conditions and therefore a coupled modelling approach is essential to solve the problem.

Project available for: PhD students

The incorporation of fractures in a rock mass model is essential to produce realistic results when making stability assessment of rock excavations such as tunnels or rock slopes. In this context, understanding the relationships between rock mass strength and fractures within the rock mass is critically important for these engineering applications.

Project available for: PhD students

The research project aims to design new electrocatalyst materials for the conversion of clean electricity (generated by solar, wind, etc) and carbon dioxide (CO2) to fuels. In this way, we can store the intermittent (i.e. unstable) renewable electricity as fuels, so we can reuse it again when needed – as normal fossil fuel except that the fuels after our approach are entirely carbon neutral.

Within this project, you will build atom-by-atom models for various catalysts on a computer, and then run simulations in order to tell if and why this catalyst material is good (or not) for the conversion of CO2 plus electricity to fuels. The figure on the righthand side is a demo of copper nanopyramids for converting CO2 to ethanol etc.

You have the freedom to choose the reaction you want to focus on, and the catalyst material you want to investigate. Your design might become real as we collaborate extensively with researchers doing experiments. We have all the learning resources to bring you on board, so don’t worry if you haven’t done molecular modelling before!

Project available for: Mphil and PhD students

However, these renewable energy resources are often intermittent; therefore, the storage of green electricity is much needed. Using electrochemical methods to realize energy conversion and storage holds great promise. These electrochemical methods can help convert green electricity–produced from renewable energy resources–to chemicals and fuels; and vice versa. My past research was focused on hydrogen evolution reaction (HER), oxygen reduction reaction (ORR), CO2 reduction reaction (CRR), and recently N2 reduction reaction (NRR), acetone hydrogenation to propane (APH) and some other reactions.

For many of these energy conversion reactions, the current bottleneck still lies in catalyst material performance–electrocatalyst with high activity and high selectivity is much-needed. Molecular modelling has been a powerful means to design new catalyst materials, by revealing fundamental level insights into the reaction activity and selectivity. However, traditional density functional theory (DFT) based calculations are based on zero kelvin and ultra-high vacuum, and are increasingly incompetent to reveal critical features of complex electrochemical reactions. We propose and advocate the Operando modelling for electrocatalysis. This project will explore further how to develop such Operando modelling techniques.

Project available for: Mphil and PhD students

This ubiquitous pathway has been implicated in the pathophysiology of major human diseases, including cancer, heart attack, stroke and metabolic disease. Oxygen-dependent enzymes act as primary sensors of oxygen levels, and the response is mediated by hypoxic inducible transcription factors. This project aims to identify key regulators of this pathway. This will exploit novel cell-based assays that we have developed for high throughput CRISPR and small molecule screens to identify novel regulators of this important pathway, and identify novel agonists and antagonists with therapeutic potential.

Project available for: Mphil and PhD students

Magnetic levitation allows completely non-contact support of isolated structures, but the inherent stability and control of complex dynamics requires substantial modelling and creativity in electromagnetic design for device optimisation and understanding their performance limits. We offer projects in this area that combine opportunities to develop new electromagnetic modelling approaches, coupled with experimental verification and validation of the vibration isolation performance of these interesting structures. Skills will be developed in mechanical and electromagnetic design, real-time control using LabView, signal processing and data analysis, optimisation, and computational modelling with dynamic simulation.

Project available for: PhD students

This project will seek to determine mechanisms of injury, using experimental and computational modelling. This will provide important data to improve injury criteria and prevention devices.

Project available for: PhD students

This project seeks to understand CSF dynamics in models of spinal trauma and disorders, using in vivo models and computational modelling.

Project available for: PhD students

This project seeks to develop novel methods to interrogate brain motion and deformation in vivo, and to explore the effect of external head loading scenarios on the brain motion and deformation.

Project available for: PhD students

Osteoarthritis is associated with joint-specific cartilage and bone changes, including to the mechanical behaviour of the tissue. This project explores the link between cartilage and bone mechanics and microstructural change in the cervical spine facet joints.

Project available for: PhD students

By measuring the gamma-ray emission from these objects (along with other astronomical data), we can determine the nature of the accelerated particles (e.g. protons or electrons) and how these particles might be accelerated.

Project available for: Mphil and PhD students

The code can be used to predict the gamma-ray, X-ray and radio emission from such accelerators, in preparation for the next-generation observatories covering these energies such as CTA, eROSITA and the SKA.

Project available for: Mphil and PhD students

We have projects using machine learning to help improve the analysis of gamma-ray data (e.g. in gamma-ray direction and energy estimation) as well as in classifying astronomical sources into certain population classes.

Project available for: Mphil and PhD students

Many techniques are developed to improve prediction accuracy using several exogenous features such as weather conditions. However, a range of factors (e.g., Future market trades, past bidding behaviour of participants, load demand uncertainty, new regulation and market roles changes etc.) potentially could help improve prediction accuracy. The objective of this project is to explore new features and use advanced ML techniques to select appropriate ones. Hopefully, in this way, we can improve price prediction accuracy.

Project available for: Mphil and PhD students

However, due to consumers' privacy concerns, limited communication bandwidth, and the cost and liability of data warehousing, only our energy consumption is recorded every 15 to 30 minutes. This is not ideal for smart grid applications that are supposed to pave our way toward a 100% renewable grid. This project aims to use the codebook dimensionality reduction technique and differential privacy theory to fix that issue. The developed method can help reduce data dimensionality, mitigate concerns around consumers' privacy and enable us to achieve the smart grid functionalities in the real world.

Project available for: Mphil and PhD students

The reason behind this regional disparity remains unknown. It is intuitive for policymakers and researchers to believe that wealthier areas or areas closer to the city where residents have a higher income must have a higher level of solar adoption compared to lower-income level areas. However, data shows the reality is too complex to be purely explained by economic factors. An example in South Australia shows that with more than 16% households having annual income above $156,000, postcode 5067 is wealthier compared to postcode 5158 that has less than 10% households with the same level of income. Postcode 5067 is also much closer to the Adelaide CBD (3km on average) than postcode 5158 (25km on average). However, only 25% buildings in 5067 have solar systems, while postcode 5158 has an astonishing rate of 52% buildings with solar panels installed. Most previous studies rely on macro statistical data to explain the regional disparity, but these studies have failed to provide consistent explanations on this confusing reality of solar panel uptake.

This project will investigate why certain building occupants have already adopted solar panels, while others have not, based on a new innovation adoption model and choice experiments.

Project available for: Mphil and PhD students

Currently, rooftop solar accounts for only 7% of Australia's 265 terawatt hours total annual electricity generation. No previous studies have forecasted the future uptake of solar PV systems in the Australian residential building sector. Without robust modelling of future solar uptake, it remains blurred and highly uncertain about whether and how the residential building sector can achieve net zero status by 2050. This project will utilise agent based modelling to simulate the diffusions of residential solar panels in Australia.

Project available for: Mphil and PhD students

Using GIS, this study maps the transition of global green building industry. Using two-mode social network analysis, this study identifies the leading organisation and key projects in the transition of the global green building industry. Based on the above, this project develops a meta-dataset of global green building industry, a GUI will be developed to assist user usage.

Project available for: Mphil and PhD students

Depending on the difficulty of the addressed problem, the projects are suitable for MPhil and PhD projects. They include:
1) Geodesic completeness of compact Lorentzian manifolds
2) Compact quotients of Lorentzian symmetric spaces
3) Homogeneity in Lorentzian geometry
4) Conformal transformation of Lorentzian manifolds

Project available for: Mphil and PhD students

This project aims to explore the potential factors and their dynamics towards the acceptance of recycled and remanufactured construction products.

Project available for: Mphil and PhD students

This species of seadragon is the marine emblem of South Australia! Its majestic shape and colours attract large numbers of Scuba divers from all over the world. The largest number of sightings are from a single region, i.e. the Gulf St. Vincent (South Australia). Although the leafy seadragon is widely known by the public, we hardly know anything about their behaviour and ecology. Unfortunately their populations are declining due to unknown reasons.

Projects are available to perform field work in the Gulf St. Vincent to study the behaviour and ecology of the leafy seadragon. In addition, projects are available to perform laboratory work using existing data to study the distribution, behaviour and ecology of the leafy seadragon.

Project available for: Mphil and PhD students

This research will involve experimental and finite element investigation into the fatigue and corrosion behaviour of key aircraft structures. The outcomes will enable safety and cost benefits to Defence and Civil aircraft operators.

Project available for: Mphil and PhD students

This project will use genetic and genomic data from modern tissues and museum skins to understand the historical phylogeography and systematics of several species in the genus Amytornis

Project available for: PhD students

Western ground parrots and night parrots are both critically endangered. This project will use genomics methods to understand population structure and genetic diversity in extant populations and help contribute to ongoing management of these unique species

Project available for: PhD students

We have previously examined diet of bats at two sites using metabarcoding of scats. This project will expand the geographic and temporal range of sampling to document seasonal and geographic changes in diet and help understand the extinction drivers in this species.

Project available for: PhD students

The cross-flow structures affect mixing and pressure distribution in the combustor. Another important parameter to investigate is the sonic fatigue and supersonic panel flutter near fuel injectors.

Project available for: Mphil and PhD students

To develop flow control methodologies to access the viability to reduce drag.

Project available for: Mphil and PhD students

The project will use experiments/simulations and AI to develop new stents aiming to improve patient outcomes.

Project available for: Mphil and PhD students

Australia has over 34000 Km of pipeline. The vast amount of energy required to pump the fluid must be reduced. Understanding turbulence is the key to solving this issue we are facing.

Project available for: Mphil and PhD students

The project aims to understand the flow dynamics is wind farms to optimise energy performance.

Project available for: Mphil and PhD students

This project aims to use comprehensive genetic and agronomic approaches to provide breeders with the tools and evidence to select WtmsDW, a newly discovered genetic region that protects pollen fertility and sustains grain yield under heat stress. The student will have access to range of resources including mutants, transgenic lines, non-destructive X-ray CT phenotyping facilities, and cereal breeding companies, delivering both fundamental and industry-relevant outcomes.

Project available for: PhD students

Working with industry partners, this project integrate state-of-the-art micro-analytical techniques, to test and develop new geochemical and mineralogical tools to assist in exploration for lithium ore deposits. A focus will be on prospective areas of the NT and SA, with the aim of sustaining Australia's supply of lithium.

Project available for: PhD students

This project will examine the inventory of cobalt in copper and nickel ore deposit from across South Australia, which will improve fundamental understanding of the geochemistry of cobalt, and how it can be extracted from ores.

Project available for: Mphil and PhD students

The research objective is to develop new game theoretic models that include uncertainties and biases in human-human and human-machine teams and to produce novel Bayesian game models with algorithms to effectively defend or attack machine learning operations.

Project available for: PhD students

Through network segmentation and segregation, the access to sensitive information, hosts and services can be restricted without affecting the organization and operation of the business. Network segmentation and segregation is one of the most effective techniques to prevent attacks and limit their impact. Today network segmentation and segregation are mainly done manually where security teams follow some guidelines that are mostly generic and require a high level of expertise.

Building on our recent work in graph partitioning algorithms and auto-configuration, we will investigate automated methods for real-time network segmentation and segregation. Most current AI solutions often indiscriminately block all network traffic on all ports and connections, rather than considering the role of each machine and the motive behind the compromise attempts as a human defender might. These solutions thus unnecessarily disable communications that are key to business operations. The main idea of the project is to develop segmentation and segregation methods that ensure operation continuity by creating a system of prevention and recovery from potential threats to the network infrastructure.

Project available for: PhD students

This project will focus on alleviating the impacts on the wellbeing, health and productivity of sheep and goats.

Project available for: Mphil and PhD students

This project aims at developing microresonator frequency combs (microcombs) with new structures and semiconductor laser pumping schemes to improve the energy efficiencies and to engineer the comb spectral profiles. Multiple applications, including gas sensing, Lidar, and free-space frequency standard transfer, will be carried out.

Project available for: Mphil and PhD students

With optical techniques, the newly generated frequency components can be detected with an ultralow noise level and measured with an ultrahigh precision. For this project, ultrahigh-quality-factor microresonators that have been utilised in precision thermometry will be used to develop electrical field sensors to detect radiofrequency and terahertz signals. In addition, we will explore the possibility of combining electrooptic effect with other nonlinear effects to test novel designs based on synthetic dimensions and parity-time symmetry breaking.

Project available for: Mphil and PhD students

With proper photo mixing technologies, the laser pulse trains can be converted into low-noise THz waves that are highly desired in telecommunication, medical and space applications. In collaboration with the Terahertz Engineering Laboratory led by A/Prof Withawat Withayachumnankul, we are working on the development of microresonator-based THz generators with high conversion efficiency and low phase noise. The generated THz waves will be employed in wireless telecommunications and space ranging systems.

Project available for: Mphil and PhD students

While proteomics analysis has widely been used to identify primary sequences of the complex mixture of proteins in snake venoms, very few studies have investigated protein interactions that contribute to biological activity. In this project we aim to use a range of structural mass spectrometry techniques to study the higher order structures of snake venom proteins to describe structural models which form the basis for better understanding of their potent bioactivities and design of novel antivenom therapies.

Project available for: Mphil and PhD students

These structures, such as triplex DNA, are proposed to naturally play a role in gene regulation, however the therapeutic potential of these unusual DNA structures are poorly explored. This project aims to develop methods to investigate and modulate DNA and RNA triple helix assembly, specificity and molecular interactions. In particular, we aim to rationally design and synthesise novel DNA triplex forming oligonucleotides which extend their capabilities for in vivo antigene applications, principally in the context of designing new antibacterial agents to address the antibacterial resistance problem.

Project available for: Mphil and PhD students

A key challenge is to detect the toxic forms of protein misfolding that arise before symptoms manifest, and to specifically target these early oligomeric species in therapeutic design. Through chemical synthesis and bioconjugation chemistry, this project aims to design novel mass spectrometry based strategies for understanding protein misfolding mechanisms, screening protein aggregation inhibitors and enabling diagnostic strategies.

Project available for: Mphil and PhD students

It is a normal biological process that enables the body to activate or silence genes in different tissue types; for instance, producing liver enzymes in the liver and brain receptors in the brain. Conversely, abnormal DNA methylation can cause disruptions to normal gene activity and progress to various diseases, ranging from congenital abnormalities that develop during pregnancy, to familial blood cancers that arise in young adolescents through to elderly adults. This project involves comparing DNA methylation changes, using array-based technologies, to identify patterns (epigenetic signatures) that are associated with the forementioned disorders. A background in biology and basic human genetics will be beneficial, albeit not compulsory, however a willingness to learn is essential.

Project available for: Mphil and PhD students

These genetic variations, at single nucleotide to small stretches of DNA sequence (SNV and Indels), are easily detectable using short-read sequencing (SRS) technologies. In ~250 families, our Australian Genomic Autopsy Study identified a genetic cause, mostly SNVs, in 50% of cases with foetal or neonatal loss. Larger copy number and structural variations (CNV and SV) were underreported, and likely reflect the limitations of SRS and reference-based approaches. This project involves constructing a graph-based method for CNV and SV detection, from a combination of short and long read sequencing technologies. Using this graph-based approach, we aim to identify previously undetected CNV and SVs that contribute to unresolved pregnancy or infant loss. A background in computer science, physics or statistics is highly desired, but a willingness to learn is the only prerequisite.

Project available for: Mphil and PhD students

However, in the financial sector overseas, there are strong regulatory constraints necessitating that decisions made by models be "explainable". This limits the use of AI in finance, and presents a huge competitive opportunity for, e.g., banks, if explainable AI methods can be developed. This project will explore explainable AI techniques and develop new approaches for improving the explain ability of AI tools applied to, e.g., credit risk scoring. We will focus particularly on Australian datasets and the Australian regulatory environment, where regulation of AI in the financial sector is still an open question. There are opportunities for top-up scholarships with this project, and the chance to work directly with industry experts.

Project available for: Mphil and PhD students

Digital health approaches show great promise, by mining online discussion forums and social media sites for a more holistic view of the patient experience of health care. The challenge is how to effectively sample these novel sources, and apply appropriate data science techniques to extract useful information. This project will look at combining traditional survey-based approaches, augmented with novel digital health techniques to build state-of-the-art views of the patient experience. We will also aim to inform public policy around health care evaluation in Australia.

Project available for: Mphil and PhD students

The science behind the observed response is not well understood, and mathematical modelling will be undertaken to increase understanding. Some knowledge of PDEs and their numerical solution is advisable for this project.

Project available for: Mphil and PhD students

Understanding this is important for separation of a mineral from a crushed ore in spiral particle sorters and for separation of cell types in microfluidic devices. The geometry of the sorter/device is key to achieving the desired separation and mathematical modelling is highly useful for understanding the dynamics and the sorter/device geometry. This project focuses on mineral processing in spiral particle sorters but could be varied depending on interest. This project will use vector calculus and PDEs; completion of a course in fluid dynamics would be beneficial.

Project available for: Mphil and PhD students

This is seen in extrusion of glass optical-fibre preforms with complex internal structure, and can affect the performance of the fibre made from the preform. In this project computational simulation will be done to improve understanding of extrudate swell in preform extrusion.

Project available for: Mphil and PhD students

Batteries have been game-changers in energy storage in which electrical energy is stored using electrochemical mechanisms. Among batteries, Lithium-ion (in short Li-ion), due to its higher energy density, is the dominating type. A full-physics mathematical model is commonly used to estimate the state of charge, energy efficiency, heat transmission and state of health in Li-ion batteries. Using such models, we can design batteries to maximise performance and longevity, under different loads and number of cycles, and also, they are often used in battery management systems (BMS) to control over-charging and over-discharging of the battery packs for a safe and efficient operation.

To estimate the abovementioned parameters, a set of inputs describing the system (battery) is required. The input parameters describe the electrochemical properties of the electrodes, electrolyte properties, diffusion, geometry, the porosity of electrodes and separator, kinetic of intercalation, resistivity of the film formed, initial condition etc. We should expect a deviation from the values provided by the manufacturer and the actual value describing the system, due to heterogeneity and the fact that the parameters change as the battery ages. Direct measurement of these parameters required dismantling the battery. Therefore, they need to be estimated by solving an inverse problem in which charging and discharging curves are the observed data. This is basically the calibration of the model for better control of the battery and a more accurate forecast. The calibration process must be computationally efficient and allow the quantification of uncertainty.

In this study, we will use a data assimilation method for model calibration. The efficiency of data assimilation methods (e.g., Ensemble Smoother) in calibrating models has been widely studied in other disciplines, e.g., weather forecasting and reservoir engineering. Data assimilation methods are popular because of their speed (requiring few simulations) and capability of providing an uncertainty assessment without additional simulation. In the project, we will use the Li-ion benchmarking battery models which are publicly available.

Project available for: Mphil and PhD students

To forecast the fate of fluids in porous rocks, needed for better management of resources and mitigation of risks, we require mathematical models. Such forecasting entails very high numerical computations and high-resolution models. This computational intensity is a big hurdle. A common practice to reduce the numerical computation intensity is to reduce the number of cells. This process is known as reduced order modelling and also upscaling. Unlike other disciplines, reduce-order modelling in porous media requires additional attention, as the medium is heterogeneous and the effective petrophysical properties for the coarsened cells must be used. Finding effective values at the coarsened scale has been a matter of research for decades. Finding effective values is a computationally intensive problem. In this project, we aim to design and apply convolutional neural networks which have been a key player in the machine learning discipline, to this problem.

Project available for: Mphil and PhD students

Recycling of spent LIBs is urgently needed to address the raised significantly economic and environmental concerns, but traditional recycling pyrometallurgy and hydrometallurgy technologies are not efficient and sustainable. The project aims to develop a green and valuable closed loop process for the recycle of end-of-life LIBs. By setting up new methods, the project will make an innovative process for "closed loop", recovering critical metal elements from batteries – especially nickel, cobalt, manganese and lithium – and reuse them in the design of a new cathode, the most expensive part of the LIBs.

Project available for: Mphil and PhD students

This aim will be realized by using a synergistic approach that integrates materials engineering, surface engineering, electrochemistry, and electrolyte design strategies. By establishing the fundamental structure-property relationships over multiple scales via advanced characterization and computation, this project will develop next-generation aqueous batteries with low cost, high capacity, and outstanding safety and durability.

Project available for: Mphil and PhD students

However, current LIBs fail to meet the increasing demands of developing technologies due to their limited battery energy densities. Therefore, it is crucial to develop high-performance cathode materials for next-generation LIBs. This project aims to comprehensively understand the mechanistic behaviours of cathode materials for LIBs and to build up systematic and detailed chemistry/structure/function relationship of active materials during battery function via a series of cutting-edge in situ/ex situ characterization technologies for their further deployment in commercialized batteries.

Project available for: PhD students

It will also be equipped to better understand the inner mechanism of applied electrodes, the criteria of electrolyte selection, and their associated interfacial reactions to build up a generalized knowledge for the further deployment in commercialized batteries.

Project available for: PhD students

This project will use wind tunnel experiments to investigate the pressure distribution over an aerofoil in dynamic stall conditions.

Project available for: Mphil and PhD students

This project will utilise large scale wind tunnel experiments to investigate this effect.

Project available for: Mphil and PhD students

In this project modelling and experimental tools will be utilised to investigate this effect.

Project available for: Mphil and PhD students

In this project a membrane less electrolyser will be developed where the ions are separated using advanced flow control methods.

Project available for: Mphil and PhD students

In this project advanced experimental methods and numerical modellings will be used to investigate this concept.

Project available for: Mphil and PhD students

Project available for: Mphil and PhD students

Project available for: Mphil and PhD students

In this project to demonstrate the feasibility of this concept a lab scale sand storage will be developed and evaluated.

Project available for: Mphil and PhD students

Project available for: Mphil and PhD students

Project available for: Mphil and PhD students

In this project the experimental facility at the micro-fluid mechanics laboratory at the University of Adelaide will be utilised to study this concept.

Project available for: Mphil and PhD students

In this project this concept will be investigated and a prototype nebuliser will be developed.

Project available for: Mphil and PhD students

Engineering is moving towards digital engineering – an integrated approach that relies on connected sources of data that support system design and production. The connected nature of this information presents an opportunity to gain useful insight into the behaviour and performance of system variants, as they emerge during design and development, in order to investigate and improve design options during operations and sustainment. This work needs to move beyond simply aiming to connect disaggregated datasets, to provide genuine insight into options analysis for systems that take important whole-of-life data into consideration. The insights that occur from this rich, connected information have the ability to inform design decisions, enhance communication, and increase understanding, while reducing risk and cost.

This project aims to identify and realise the potential benefits of this connected data through the use of digital threads that support advanced data analytics within and across related but previously stove-piped areas. The research will benchmark the current state of digital engineering practice, before identifying key areas for exploring and exploiting the rich nature of the information captured. Practical, scalable and secure methods will then be developed to exploit these areas within a pilot project. This work will then be extended to solve the general case for a highly connected, cross-platform digital engineering environments to produce a widely applicable methodology for the realisation of engineered systems.

Project available for: PhD students

Their complex physiology renders treatment difficult but what is clear is the importance of lipids in the brain. Using cell models of brain disaese and latest mass spectrometry technologies, this project aims to interogate lipid metablism within the brain to gain mechanistic information and identify new avenues for treatment.

Project available for: Mphil and PhD students

This project will use cell models of osteoblasts (bone forming cells) and osteoclasts (bone remodelling cells) to understand bone dynamics with the ultimate aim of uncovering new opportunities for therapeutic intervention.

Project available for: Mphil and PhD students

While its advancement faces the great challenge of the unsatisfactory lifespan of the Zn anode due to the uneven distributions of Zn plating, severe chemical corrosion in the aqueous electrolyte, and narrow electrochemically stable potential windows (ESW). This project amins at developing new electrolyte systems to enable high-energy-density ZIBs with long cycle life and good safety performance. The target electrolyte systems include but not limit to organic/inorganic hybrid electrolytes, electrolyte additives, high concentration electrolytes. Co-researcher: Shilin Zhang

Project available for: PhD students

Co-researcher: Shilin Zhang

Project available for: PhD students

This project aims to understand the crystal reconstruction of the functional electrocatalysts in CO2 reduction reactions. Several copper-complex materials for electrocatalytic carbon dioxide reduction will be proposed. Detailed analysis will be provided toward designing metal-complex molecular structures for controllably generating active species under reaction conditions to catalyse desirable chemistry.

Co-researcher: Shilin Zhang

Project available for: PhD students

As a key component of the Standard Model of the Universe, QCD describes the interactions between quarks and gluons as they compose the proton, neutron and a great zoo of other particles. To explore QCD from the fundamental first-principles of the theory, the ab-initio approach of Lattice QCD is used, where numerical simulations of the quantum field theory are performed on supercomputers. Visualisations of this emergent phenomena are key to understanding the complexity. In relating the results of Lattice QCD to the experimental measurements of nature, a nonperturbative extension of chiral effective field theory is developed. It provides a systematic approach based on observed degrees of freedom and is complementary to ab-initio lattice QCD. Projects will draw on these techniques to address contemporary challenges at the fore of the field.

Project available for: Mphil and PhD students

The main responsibility is to perform the analysis of genetic and clinical data obtained from the International Consortium on Lithium Genetics (112 scientists) and the International SSRI Pharmacogenomics Consortium (35 scientists).

Project available for: PhD students

This project is co-designed in consultation with the leaders of Multicultural Communities. Limited involvement of CALD communities in genomic research is documented both in Australia[7] and globally[8-10]. To date, 60-88% of genetic studies have been based on the genomics of people sampled from European ancestry populations[8] with only 3.8% of studies involving Africans, Hispanic or Indigenous people[10]. The reason for the continued low representation of diverse populations is likely multifactorial. First, existing large biobank cohorts such as the UK Biobank (UKBB) are largely made up of people of European ancestries. Second, researchers have been focusing on populations of homogeneous ancestry due to easier data collection and analysis, and the limitations of funding to enrol more diverse groups in genomic studies. Third, there is a lack of diversity in the research workforce and a history of discrimination in some communities[11].

Increasing evidence strongly indicates that there are ethnicity-specific genomic loci implicated in a wide range of complex health outcomes[10]. This underrepresentation of CALD populations in genetic studies limits the capacity to study population-specific genetic variation, and creates a critical bottleneck for the translation of genomic knowledge into diverse populations[8-10]. In countries such as Australia where more than 26% of its citizens come from ancestries other than white European[12], the lack of diversity in genomic research exacerbates health inequalities by limiting the generalisability and translation of research findings into the clinical care of CALD communities

Project available for: Mphil and PhD students

The emergence and spread of multidrug-resistant Salmonella calls for new strategies to prevent foodborne disease. This project will advance an innovative antimicrobial strategy using cold plasma technology for drug-free egg and chicken meat treatment to ensure food safety and improve animal welfare.

This project is in collaboration with Dr Andrea McWhorter (Salmonella expert, veterinary scientist).

Project available for: Mphil and PhD students

This project will advance a novel medical device using a laser to kill bacteria/viruses towards clinical trials. This includes in vitro/in vivo validation of the medical device, prototype development and potentially a first-in-human pilot study to improve health outcomes of patients with superbug infections.

This project is in collaboration with Dr Roman Kostecki and Prof Heike Ebendorff-Heidepriem (photonics experts) at the Institute for Photonics and Advanced Sensing.

Project available for: Mphil and PhD students

Our laboratory is involved in a number of clinical trials and the measurement of biomarkers as an objective assessment of effectiveness. One significant challenge is the progressive nature of disease which means that any treatment is challenged with a residual disease burden that exists prior to diagnosis. Students have the opportunity to join a number of research programs aimed at understanding pathological mechanisms of brain disease in their choice of cell models, patient samples and/or mouse models of disease.

Project available for: Mphil and PhD students

This work is aimed to propose a new solution based on the analysis of probabilistic automata models (also known as labelled Markov chains) discovered from event data. The main contribution of the work is the application of the existing and developing new algorithms for finding distances between probabilistic automata models.

Project available for: Mphil students

Process mining is a data analysis area that studies methods for the discovery of process models from event data. The discovered models can be further analysed, e.g., used for the prediction and classification of the users’ behaviours. The aim of this work is to apply process discovery and analysis techniques in the social network context to classify and predict the behaviour of users.

Project available for: Mphil students

These event logs contain names of activities together with their timestamps. The durations of activities can vary and follow specific probability distributions. Depending on these distributions the type of process models, e.g., Markov, semi-Markov processes, or stochastic Petri nets, that represent the system’s behaviour, can be selected. The goal of this work is to analyse event logs of real-world information systems and study the probability distributions of activity execution times. Then basing on the results of this analysis a framework that assists in selecting the type of process models discovered will be developed.

Project available for: Mphil students

Limiting probabilities are widely used in the analysis of Markov chains. Markov chains discovered from real-world event data are usually large models containing considerable number of states and transitions. The aim of this project is to develop an efficient and precise algorithm for the calculation of limiting probabilities. The algorithm will use the divide-and-conquer approach and its correctness will be provided

Project available for: Mphil students

This project is aimed at the discovery of hidden Markov models considering event traces as sequences of observed events. The main challenge of the approach will be to learn hidden unobservable states of the process that influence the sequences of events in the event log. The approach will be parameterised by the number of hidden states.

Project available for: Mphil students

The existing measures for the entropy rate estimation are time consuming and are usually biased. RNNs is a useful tool that predicts the next state of the system observing the inputs and the previous system’s states. The aim of this project is to assess the applicability of RNNs to estimate the entropy rate of a language.

Project available for: Mphil students

Project available for: PhD students

By understanding the enzymology, chemistry, and microbiology of a key set of enzymes involved in steroid metabolism and developing strategies to block this activity, we aim develop therapeutic targets. This project is essential to develop effective strategies to combat the effects of pathogenic bacteria which use cholesterol and may have future applications in the treatment of diseases such as Buruli ulcer and tuberculosis. We also study the enzymes involved in mammalian steroid hormone formation which can be used to develop inhibitors with uses in treating prostate cancer.

Project available for: Mphil and PhD students

They are involved in respiratory processes to produce chemical energy within the cell, pathways to build large molecules from smaller substrates (anabolic) and the breakdown of molecules into smaller species for cellular metabolism (catabolic). Microorganisms such as bacteria represent the most diverse branch of life being found in every environment on earth capable of supporting life. The electron transfer to the monooxygenase enzymes in bacteria is tightly regulated by ferredoxin (iron-sulphur cluster) proteins. This project will unravel electron transfer processes important to these processes. It will involve the of study new enzymes and the associated ferredoxins from bacteria found in interesting environments (or genes from metagenomes) which carry out novel reactions. We also have project that interrogate the mechanism of these enzymatic processes using experimental techniques (synthesis, biochemistry, structural biology) and theory (with collaborators).

Project available for: Mphil and PhD students

Bacteria that can grow in different environments have evolved to utilise and synthesise a broad range of chemicals. The utilisation of bacterial enzymes for synthesis has many advantages over chemical systems (mild conditions, improved selectivity, less waste). The aim of these projects is to delineate the function of enzymes from bacteria. The goal is to find molecules which bind with a preference for selective activity, or to adapt the enzyme to achieve this, and to determine the products. A number of different chemical classes will be targeted including terpenoid compounds to generate flavour and fragrance or medicinal compounds, alkanes and halogenated aromatics for bioremediation. Alternatively we can also alter the product selectivity by protein engineering the enzymes.

Project available for: Mphil and PhD students

We have projects available using and designing enzymes for applications in lignin valorisation, plastic degration and fine chemical synthesis. We use protein engineering, molecular biology and structural biology to construct enzymes and biological systems that can carry out these chemical process more efficiently.

Project available for: Mphil and PhD students

It is part of a larger and long term multi-disciplinary research project which involves collaborators across biology, mathematics, field robotics and computer sciences.

Project available for: PhD students

Project available for: Mphil and PhD students

Maintenance and operation of these facilities involves controlled releases of small quantities of radioactive material into the environment and increases the risk of radiation exposure to the public and environment. Atmospheric releases of radionuclides such as the noble gas krypton-85 can be monitored using the advanced laser-based measurement technology Atom Trap Trace Analysis (ATTA) that is being developed at IPAS. This PhD project will develop a mobile radiokrypton gas sampling capability that can be deployed on-shore and off-shore and analysis of samples using the ATTA facility.

Project available for: PhD students

Because ATTA is extremely isotope selective it has become a powerful tool for radiometric dating in hydrology, where it is used for measuring the concentrations of the long-lived tracers 85Kr, 81Kr, and 39Ar. These noble gas radionuclides present as nearly ideal tracers; they are chemically inert and are thus not involved in geochemical processes and cover a broad range of dating ages due to their relevant half-lives.

The project will investigate how best to implement laser cooling and atom-optical tools for optimizing the count rate and thus the sensitivity of the ATTA.

Project available for: PhD students

Remote mining accommodation in Australia is typically constructed as prefabricated Transportables with a high energy use in production and operation. The project will investigate how this energy use can be reduced and will consider the life cycle of the construction materials during production and after mining operations are completed.

Project available for: Mphil and PhD students

The project will use a suite of innovative techniques, blending artificial tagging and telemetry, with information extracted from the chemical composition of otoliths (i.e., fish ear bones) to better inform environmental and fisheries management. These remarkable structures provide a time-resolved record of both individual growth and environment histories that can be read using laser ablation mass spectrometry (LA-ICPMS). Harnessing the power of these complementary approaches will provide critical insight on the key habitats contributing to the replenishment of South Australia's golden perch fishery. Ultimately resolving how fish movement together with habitat and flow-related environmental conditions influence fishery production and stock structure is critical to supporting evidence-based decision-making.

A top-up scholarship may be available subject to funding approval.

Project available for: PhD students

The key point is to treat well with some solute and promote attraction particle-rock. The work includes flow tests with colloidal-suspension fluids in visualisation cell, observations under the microscope, filming, and analysing the results. The project also encompasses evaluation of electrostatic forces and detachment management by component concentration alternation alteration during CO2 and hydrogen injection.

This Chemical-Petroleum Engineering project is continuation of 2016-2021 honours projects supported by Santos (SA) and Wintershall (Germany).

Project available for: Mphil and PhD students

The laboratory protocol and mathematical lab-data-treatment method have been applied for model Berea sandstone. The present project aims application of the methodology to real reservoir cores. The work includes laboratory core floods for water-gas and water-oil fluids, analysis of SEM, XRD, and EMX results, data treatment and improvement of the newly developed method.

The project is sponsored by Wintershall (Germany).

Project available for: Mphil and PhD students

The essence of the project is the derivation of exact solutions for two-phase flow under chemical reactions and stratigraphic entrapment. The student will be provided by main explicit formula. The scope of project will be the obtaining of field case data from industrial literature, applying the analytical solutions and comparison with 3D reservoir simulation. The project is continuation of several honours and industrial projects carried out since 2012. Publication and direct industrial application of the project result are expected.

Project available for: Mphil and PhD students

These changes, formally termed as climate change, have become one of the most pressing issues of our era. Climate science involves analyzing and monitoring data from different sources such as earth-orbiting satellites, model simulations, and in situ observations. With the passage of time, the climate data has increased significantly in terms of its volume, velocity, and variety. Unlike, other domains such as healthcare, there is very little adoption of big data technologies in the field of climate science to deal with such massive data.

This project aims to collect climate data from different sources (e.g., model simulations, satellite data, and weather data). Then, the project aims to analyze the data using big data technologies (e.g., Hadoop, Spark, and Kafka) in a streaming fashion to extract insight from the data in real-time. The project will use machine learning, natural language processing, and various data analysis techniques to analyze the data for extracting valuable insights.

Project available for: Mphil and PhD students

In 2020, 32,000 data exfiltration incidents have been reported. The primary reason for these incidents is the inability to detect attacks in real-time. This project aims to utilize big data technologies (e.g., Hadoop and Spark) for developing a cybersecurity system that can accurately detect data exfiltration attacks in real-time. The project will be developed using our big data infrastructure consisting of private clouds, container technologies, and Microsoft Azure. The project will leverage Data Mining, Machine Learning (ML), and Natural Processing Language (NLP) for detecting cybersecurity attacks using data exfiltration datasets.

Project available for: Mphil and PhD students

But how exactly do these emerging data streams help inform on-farm decisions? While more high-quality data theoretically enables improved farm outcomes (e.g., productivity, sustainability), it is often not so simple in practice, due to the complex relationships between biophysical variables being measured, operational decisions and farm outcomes. To realise the full potential of digital agriculture, the application of data science and information technologies that are capable of bridging the gap between data and decisions needs to be prioritised.

This project will use innovative modelling and data analytics (e.g., biophysical simulation, data-model fusion, machine learning) to develop digital environments—that build on a prototype already developed—for on-farm decision support. The digital environment will optimally combine diverse data streams (e.g., plant and soil sensors) with models that capture our understanding of biophysical farm relationships, therefore creating a unified depiction of what is happening on-farm, why, and what is likely to happen in the future. It will also provide a basis for evaluating ‘what if’ scenarios pertaining to different operational decisions (e.g., fertilizer application rates) as well as a changing climate and financial markets. Several applications that are critical to Australia’s agriculture industry will be considered as case studies (e.g., grains, horticulture).

Project available for: PhD students

Never before have agrifood supply chains been so complex. With increasing complexity comes increasing risk of failure (e.g., supply shortfall, reduced market access), exacerbated by current geopolitical uncertainty and a changing climate. Our agrifood supply chains will likely need to continue to operate beyond the conditions in which they were originally designed. Having learned about agrifood supply chain vulnerabilities during COVID-19, now represents an opportune time to rethink the design and management of agrifood supply chains. Increased efficiencies and circularity within supply chains via utilisation of wastes and by-products represents a critical means to enhance supply chain functioning in the face of uncertainties.

This project will adopt a ‘systems thinking’ approach, focusing on the interaction between actors (e.g., producers, retailers) across the supply chain, to evaluate the performance of supply chains under different design and management decisions and how effective different food waste prevention and reduction technologies are at enhancing circularity. Several agrifood supply chains that are critical to Australia’s agriculture industry will be considered as case studies.

The project will adopt a combination of system dynamics modelling and multi-objective optimization approaches to identify supply chain design and management decisions that achieve optimal trade-offs between reliability, robustness and resilience (R3). The project will aim to provide answers to questions such as “How should food waste reduction technologies be incorporated into food supply chains while also ensuring adaptive capacity?” as well as "How diversified should Australia’s agrifood supply chains be going forward?" and "How contrasting are the objectives of different actors within supply chains?"

Project available for: PhD students

When combined with emerging rare earth ion transitions and precise excitation processes, this project will help solve an important problem in optics; that the overall efficiency and power produced from deep mid-infrared light sources is not sufficient for all industries. The primary outcome will be a series of robust fibre-based gain modules suitable for high power and very short optical pulses in the mid-infrared. These light sources will beneficially impact medicine, defence, sensing and manufacturing providing excellent opportunities for increasing Australian productivity and global competitiveness.

Project available for: Mphil and PhD students

This project will look to develop these structures in soft-glass using the extrusion method, where glass is pushed through a metal die under pressure to create features in the glass. These fibres have a range of applications, including non-invasive sensing methods like Raman or light delivery for infrared or ultrashort lasers. This project would suit someone with a background or interest in optics or glass development. This will use some of the specialist glass processing and manufacturing facilities available at the Institute of Photonics and Advanced Sensing.

Project available for: Mphil and PhD students

Methods which don’t change the biological processes are an ideal way to avoid this, using techniques like DHM to get an image of the refractive index profile of cells and structures. DHM creates an image using interference, so is extremely sensible to small changes. This project will expand on previous work in DHM, adapting the setup to involve multiple-passes through the sample to further enhance the method. This project would suit someone with a background in Optics or engineering/data analysis/machine learning. This work will be done in the Centre of Light for Life, in new specialist labs as part of a larger research team comprising physicists, chemists, biologists and medical researchers with the goal of translating fundamental science to application.

Project available for: Mphil and PhD students

Lightsheet however is normally limited to large, bulky systems meaning that measurements can only be done on small subjects or dead cells. This project will look to combine lightsheet imaging with fibre optics, such that this method can be applied in-vivo or in otherwise difficult to reach locations. This work will be done in the Centre of Light for Life, in new specialist labs as part of a larger research team comprising physicists, chemists, biologists and medical researchers with the goal of translating fundamental science to application.

Project available for: Mphil and PhD students

We are exploring the limits of a speckle pattern-based wavemeter, aiming to achieve a measurement precision better than an attometre, opening the door to many fundamental and applied experiments.

Project available for: Mphil and PhD students

To avoid this, the quantum properties of light can be utilised to image a sample with single photons. Join us in setting up this research project and work alongside optical physicists and biologist and a transdisciplinary group.

Project available for: Mphil and PhD students

We have samples and data on over 230 families and have identified genetic causes in ~25% cases. We and others continue to find new variants associated with blood cancers in known predisposition genes such as GATA2 and RUNX1 that are difficult to classify as pathogenic or benign without performing time-consuming and expensive assays. In this project, we will use state-of-the-art genomics technologies and bioinformatics analyses together with elegant functional assays to develop a single multiplex assay of variant effect (MAVE) to determine the pathogenicity of every possible amino acid change in both GATA2 and RUNX1. The aim is to provide an invaluable resource for clinicians, diagnosticians and researchers worldwide who deal with predisposition to blood cancers (and some solid cancers) to benefit family and patient management.

Project available for: Mphil and PhD students

Many techniques are developed to improve prediction accuracy using several exogenous features such as weather conditions. However, a range of factors (e.g., Future market trades, past bidding behaviour of participants, load demand uncertainty, new regulation and market roles changes etc.) potentially could help improve prediction accuracy.

The objective of this project is to explore new features and use advanced ML techniques to select appropriate ones. Hopefully, in this way, we can improve price prediction accuracy.

Project available for: Mphil and PhD students

However, due to consumers' privacy concerns, limited communication bandwidth, and the cost and liability of data warehousing, only our energy consumption is recorded every 15 to 30 minutes. This is not ideal for smart grid applications that are supposed to pave our way toward a 100% renewable grid. This project aims to use the codebook dimensionality reduction technique and differential privacy theory to fix that issue. The developed method can help reduce data dimensionality, mitigate concerns around consumers' privacy and enable us to achieve the smart grid functionalities in the real world.

Project available for: Mphil and PhD students

Due to the complexity of the e-fleet and the potential for automation and prognosis, we need dynamic representations of the e-fleet to optimise mining operations in real-time and improve performance. This project's main objective is to develop a data-driven digital twin for mobile electric fleets where trucks, loaders, and other vehicles interact with stationary systems and energy supply, storage and distribution networks. The twin includes electric vehicles, energy devices/assets, monitoring/controlling multiple devices, simulating mining operations, and real-time productivity optimisation relying on clean energy sources. The final product will be a replicable, innovative solution to be integrated into electric mines in Australia and contribute to sustainable mining.

Project available for: Mphil and PhD students

At present, most of the similar schemes use a visual inspection system which makes the system expensive and unsuitable for privacy-sensitive areas. Therefore, we propose a smart solution based on infrared through-beam sensor arrays combined with Lidar systems. By advanced modelling, the position of the elderly in the room can be determined, and the data of the elderly's normal behavior can be modeled and compared, so that any fails can be determined and alarmed to save lives.

Project available for: PhD students

But their health monitoring is only based on regular scheduled checks which only occur when the machine is off-line. With the wireless technology and advanced dynamic vibration modelling, it is the purpose of this project to show the innovative online measurement that allows simple integrity detection of rotary machine without taking them offline.

Project available for: PhD students

a farming method applying information technology to minimise resources used and maximise quality, yield and land utilisation. Organic matter, mineral and moisture compositions of soils are essential information for the sustainable management of soils providing farmers insights to improve productivity and maintain optimal soil health. This research aims to develop an in-situ soil sampling system based on an autonomous agriculture tractor. The project encompasses a smart NIR sensing system to collect soil samples to depths of 500 mm; an intelligent model analysing the samples in real-time; and a digital system to collect and store the soil information with the provided GPS information on the tractor.

Project available for: Mphil and PhD students

Recent advances in dictionary learning, in which a dictionary adapts its atoms to training data, hold great promise for improved performance for many areas of signal processing. This project explores the idea of using coupled dictionaries for processing radar data, such as clutter suppression and target extraction. It is expected that successfully trained dictionaries are capable of improving real-world performance of radar surveillance systems.

Project available for: PhD students

The receiver captures backscatter from the target(s) of interest but they also contain clutter, or returns from other objects in the environment. The presence of clutter often make the task of detecting targets harder. Statistical techniques are used to discriminate target from clutter. The study such detectors depend on the availability of radar data. However, capturing data from real radars involve costly trials, beyond the capability of most researchers.

In recent years, machine learning techniques have been very successful in producing highly realistic synthetic data. This project involves using established machine learning techniques such as auto-encoders and generative adversarial networks (GANs) to generate realistic clutter data for maritime radar applications. The generated outputs will be compared with known statistical properties from real radars. Successful simulations will provide a cost effective method to enhance the progress of future radar research.

Project available for: PhD students

However, establishing urban forests in a rapid and meaningful way is difficult. Impediments include the cost and acquisition of land, the maintenance, and protection of the constructed ecosystem, ongoing funding sources, and the socio-ecological design of the forest. This project sits at the intersection of these challenges combining urban forestry, horticulture, and landscape architecture knowledge. The project aims to re-introduce relic and threatened species into the metropolitan area of Adelaide, and other cities, through the establishment of patches of urban forest that support the long-term survival of the species and associated ecologies. Adelaide has amongst the fewest remnant patches of endemic vegetation of any of Australia's capital cities. The project will therefore examine methods of rapid urban greening and monitoring through evaluation of best practices from around the world

Project available for: PhD students

Digital Twin approaches have great potential for better understanding of the more-than-human dimensions of our cities, yet consideration of urban ecology and biodiversity has remained peripheral to smart cities research. The technology presents significant potential for analyzing current conditions and for modelling and simulating future biodiversity and climate conditions.

This project aims to apply emerging Lidar with IoT technologies to create digital twins of cultural forests for a range of applications frome art based projects to citizen science. Applicants should have a passion and demonstrated track record in related technologies and nature-based systems and a creative capacity to bring together both design and science. The project is a joint collaboration with UNSW Sydney and applicants will be supported by both institutions.

Project available for: PhD students

However, implementing such systems in a culturally and ecologically meaningful and enduring way is far from straightforward. Urban ecological systems are typically being degraded in cities around the world including those of Australia. This project seeks to identify best practice principles for green infrastructure through building up a database of Park Systems around the world. Park Systems are integrated and designed green spaces that are accessible and aligned with the underlying ecological structures of urban areas. Landscape architects, architects, urban planners, ecologists, and engineers who would like to develop expertise in these systems can apply. Applicants should have a strong peer reviewed publication record and portfolio of landscape design or environmental planning projects.

Project available for: PhD students

We will use advanced spectroscopy to characterize the fibre laser dynamics, computer modelling to optimize the laser design, and demonstrate the concept experimentally. The new design will enable agile, high precision polymer processing tailored to the unique absorption lines of carbon-hydrogen bonds in different polymers where there is currently a lack of high power, high brightness low-cost light sources. It will also open the door for very high resolution laser assisted glass 3D printing.

Two PHD scholarships are available for an immediate start. The project involves both hands-on work with fibre lasers and optical systems as well as numerical and theoretical aspects. Spectroscopy, laser design and construction and numerical optimisation will be conducted under the guidance of the supervisors. The new lasers designs developed will be applied to polymer and glass 3D printing applications.

Project available for: PhD students

These systems may be vulnerable to changes in multiple statistical attributes of climatic variables. Scenario-neutral climate stress-testing approaches provide a means to enhance understanding of the complex mechanisms by which a system might respond to climatic changes, compared to traditional scenario-driven approaches. They also allow for identification of management or design options that achieve desired system performance. This project will employ scenario-neutral climate stress-testing to better understand the sensitivity of performance metrics for several agricultural systems (e.g., different crop and livestock enterprises, different agroecological regions). Through inverse modelling, this project will identify management and design options that are likely to improve agricultural system performance. This project is part of ongoing development and application of research tools to model changes in the attributes of hydro-climatic time series to facilitate climate impact assessment.

Project available for: PhD students

This will overcome the limitations of existing damage detection techniques. The outcome of this project will significantly improve the capability and practicability over existing inspection technologies adopted by industry for a wide range of infrastructure, such as the civil, building, mechanical, and oil and gas infrastructure, as well as improving the reliability and cost efficiency of the inspection.

Project available for: Mphil and PhD students

These techniques will provide non-contact inspection for a wide range of infrastructures. The outcome of this project will allow inspection of structures with poor surface or hard-to-inspect conditions. This will significantly increase the practicability and reliability of the inspection. Ures using nonlinear ultrasonic guided waves

Project available for: Mphil and PhD students

We expect this project will lead to the adoption of ML models in clinical routine by estimating risks based on more reliable features and providing explain ability about the prediction. The data modalities for this project may include multi-modal medical data such as imaging data, structured health record data, and possible medical reports. In the field of preventive medicine, we expect the markers produced by the risk prediction model will guide other scientific fields onto novel directions to tackle abnormality development.

Project available for: PhD students

There is an increased interest in learning more explainable models, including causal models. In this project at the Centre for Augmented Reasoning, we aim to use machine learning and computer vision to achieve the automation of core capabilities of a bioinformatician, which could lead to a real-time data and patient characterisation platform for researchers and clinicians.

Project available for: PhD students

Becoming an entrepreneur entails risk-bearing, an increased workload, and increased levels of stress. Around 40% of new companies will fail within the first year and failure can have severe financial and personal consequences, resulting in common symptoms such as insomnia, tiredness, pain and stomach problems. However, few research has been done on the mental health of entrepreneurs. The present study aims to jumpstart research in this area.

Project available for: Mphil and PhD students

Novel measures of video processing to enhance diagnostic methods, identify new variables, tracking progress of illness, response to treatments and improve the accuracy of predictions in people who are at risk of psychosis will be achieved. There is potential for collaborations with psychiatric clinics in Adelaide and Australia.

Project available for: Mphil and PhD students

This project aims to characterise the role of genetic factors and its functional and structural brain correlates in distinct aspects of cognitive functioning using the UK Biobank data.

Project available for: Mphil and PhD students

Early diagnosis leads to removal of these lesions/polyps using different minimally invasive interventional strategies which Professor Singh performs.

Project available for: Mphil and PhD students

Key techniques and methods involved include: experimental stroke model, behavioural outcome assessment, immunohistochemistry, ELISA, MRI.

Available to one student only.

Project available for: Mphil and PhD students

Key techniques and methods include: experimental stroke model, behavioural outcome assessment, MRI, physiological monitoring, immunohistochemistry, ELISA.

This project is open to 1-2 students

Project available for: Mphil and PhD students

Key techniques and methods include: clinically-relevant stroke model, physiological monitoring, behavioural outcome assessment, MRI, immunohistochemistry, ELISA. This project is open to 1 student.

Project available for: Mphil and PhD students

A critical problem is the capacity of the human to understand information from the AI agent, and the capacity of the AI agent to understand the responses of the human. It is therefore important to develop systems that support hybrid human-AI teams. In this project, you will focus on understanding how to abstract human performance into metrics that describe human performance for different tasks. You will also work on modelling this behaviour, and developing models to promote exchange of information between the human and AI agent. Your work on this multi agent system will also likely involve game theory. We welcome applicants from behavioural science (e.g. psychology, neuroscience), computer science, mathematics or engineering. Training in modelling and behavioural science will be part of this project. We look forward to hearing from you. Applicants must have Australian citizenship or permanent residence.

This work is part of a collaboration with DSTG. Co-researcher: Prof Lang White (Electrical engineering and the Teletraffic Research Centre, Adelaide Uni)

The underlying molecular biology is poorly understood and current therapies are highly damaging to the children. This project is part of a national multidisciplinary collaboration aimed at understanding this complexity in order to find new treatment options and targets for precision medicine. The project takes a multi-omics approach to determining the different biological origins of neuroblastoma tumours and determining new tumour subtypes. The candidate will gain experience in analysis of gene expression, circRNA expression, miRNA expression and alternative splicing, and with both bulk and single cell analyses.

Project available for: Mphil and PhD students

We have now found that several circRNAs contribute to intracellular activities that drive cancer formation. We propose here to determine how the circRNAs influence these processes, and also to determine how these particular circRNAs are made in the cell. In particular, this project involves bioinformatic evaluation of each of six potential ways circRNAs may be functioning, including as miRNA sponges, translation, cis-regulation and protein complex scaffolding.

The student will gain experience with analysis of gene and circRNA expression, protein expression (Mass Spectrometry) and HITS-CLIP data. These studies could reveal new mechanisms that contribute to cancer initiation and progression.

Project available for: Mphil and PhD students

Project funding: Australian Research Council.

Project available for: PhD students

Impact of atmospheric boundary layer (ABL) turbulence through wind-induced displacements of heliostat structure on slope and tracking error of heliostats will be investigated through field-scale measurements to improve heliostat field performance.

Project available for: Mphil and PhD students

Project available for: Mphil and PhD students

Early diagnosis leads to removal of these lesions/polyps using different minimally invasive interventional strategies which Professor Singh performs.

Project available for: Mphil and PhD students

Aesthetic and biocompatible ceramics are used as crowns and bridges. However, due to the brittleness of ceramics, ceramic crowns and bridges suffer from manufacturing-induced surface damage with current dental CAD/CAM techniques. This project aims to explore new manufacturing techniques to produce high-quality restorations made of advanced materials using cutting-edge manufacturing and materials facilities. The project will train the students to enhance their skills in advanced materials and manufacturing.

Project available for: Mphil and PhD students

This project aims to develop rapid 3D printing techniques for titanium alloys to meet their wide application demand. It will focus on the establishment of the process-microstructure-property relations to maximize the functions of the materials using advanced manufacturing and materials facilities. The project will train the students to enhance their skills in advanced materials and manufacturing.

Project available for: Mphil and PhD students

Project available for: Mphil and PhD students

Project available for: Mphil and PhD students

Project available for: Mphil and PhD students

Nasal irrigation using bottle wash, nasal sprays, and conventional nebulisers are the available sinus drug delivery methods that have an efficiency of less than 3%. Our recent studies have shown that the application of acoustic waves in sinus drug delivery can improve the efficiency of drug delivery to maxillary sinuses more than 45-fold compared to the conventional nebulisation delivery method.

Aim: This project aims to develop a high-fidelity computational fluid dynamics model to understand the mechanism underlying the acoustic drug delivery technique to optimise this novel technique for drug delivery to other paranasal sinuses (e.g., frontal, ethmoid, and sphenoid sinuses).

Project available for: Mphil and PhD students

It is crucial to do the operation in a way that the patients do not get difficulties in breathing, as well as the post-operative sinuses be accessible enough for effective topical drug delivery.

Aim: In this project, several different ESS methods will be simulated through VESS using CFD models to optimise the ESS for better drug delivery to sinuses using the acoustic-mediated delivery method.

Project available for: Mphil and PhD students

Preventable metabolic conditions, such as obesity, can be tackled by creating healthier but desirable foods.

Negative sensory attributes e.g. astringency and bitterness, drive food choice and are important to many food industries (e.g. tea, wine and chocolate).

This project aims to identify links between inter-individual astringency and bitterness perception, and salivary proteome, genetics and oral-microflora using MassARRAY gene-profiling, novel phenotyping and segmentation bases, biophysical characterisation and new microbiome techniques, e.g. 16S rRNA gene sequencing.

The project provides training for a PhD candidate in genetic and proteomic analysis, sensory science, oral microbiomics, physical aspects of protein binding and predictive modelling.

Project available for: PhD students

Further information about the Alliance and the Joint PhD scheme can be found here: Jointly awarded PhDs with the University of Nottingham

Critical to fighting the threat locusts pose to food security are improved methods for detecting the onset of swarming behaviour, and developing more effective interventions (e.g. barrier spraying).

This project will develop a data science framework to quantify swarming patterns in locusts using tracking data collected in the field, enabling us to identify the distinctive patterns associated with the onset of damaging swarm formation.

This, in turn, will inform the development of state-of-the-art agent-based models for swarm , which will allow us to predict the effect of different interventions. A background in either mathematics or statistics, and familiarity with a programming language will be an advantage. No previous knowledge of locust behaviour is required.

Project available for: PhD students

Further information about the Alliance and the Joint PhD scheme can be found here: Jointly awarded PhDs with the University of Nottingham

Pectin, the major non-cellulosic polysaccharide in many plant-cell walls, plays significant roles in the organoleptic properties of food and wine.

It is composed of polymers of monosaccharides, assembled in vivo by a complex array of more than 50 glycosyltransferase enzymes, few of which have been characterised.

The research proposed seeks to identify and characterise pectin biosynthesis glycosyltransferases from major crops including grapevine and apple, using a combination of molecular and biochemical approaches.

Mechanisms of pectin biosynthesis and its regulation will be investigated, to allow the development of strategies to optimise pectin composition, content and extraction for food and wine production.

Project available for: PhD students

Further information about the Alliance and the Joint PhD scheme can be found here: Jointly awarded PhDs with the University of Nottingham

This project will investigate the relationship between sweet taste perception and intestinal glucose absorption as a possible predictor of future issues with postprandial glucose control and type 2 diabetes.

Project available for: PhD students

Further information about the Alliance and the Joint PhD scheme can be found here: Jointly awarded PhDs with the University of Nottingham

Strains of yeast used in the wine fermentation process can be enhanced through directed evolution in lab biostats.

Starting strains are exposed poor nutritional or alcohol rich environments: those that survive these harsh environments can then be used in subsequent experiments, re-enforcing desirable genetic traits.

In this project, we will develop stochastic and deterministic mathematical models of the dynamics of yeast strains bred in these conditions. The aim is to optimise experimental conditions that maximise the evolution of yeast suitable for use in the wine fermentation process. A background in applied mathematics and knowledge of computer programming will be required.

Project available for: PhD students

Further information about the Alliance and the Joint PhD scheme can be found here: Jointly awarded PhDs with the University of Nottingham

Biofilms are communities of microorganisms living in a protective layer of slime, known as EPS (extracellular polymeric substances). They can be both problematic (e.g. contamination of medical implants) and beneficial (e.g. waste water treatment).

This project will use mathematical modelling to understand why biofilms expand at different rates when cultured on agar of different water content. Our hypothesis is that EPS production can assist biofilm expansion by pulling water into the biofilm from the agar by osmosis, and that this may also increase nutrient delivery to the biofilm. A background in applied mathematics, physics or engineering will be helpful.

Project available for: PhD students

Further information about the Alliance and the Joint PhD scheme can be found here: Jointly awarded PhDs with the University of Nottingham

Lactic acid bacteria (LAB) are essential to the global wine and dairy industries. However, transformation systems in LAB are inefficient and not used routinely. This is inhibiting both applied and fundamental research in LAB.

This project will; investigate the fundamental reasons for transformation resistance in the LAB Oenococcus oeni, develop a reliable method for genetic modification of wine LAB (including O. oeni), and utilise and improve systems from dairy lactic acid bacteria. This project will provide a toolbox for LAB researchers to understand the genes necessary for both fermentation reliability and aroma modification.

Project available for: PhD students

Further information about the Alliance and the Joint PhD scheme can be found here: Jointly awarded PhDs with the University of Nottingham

This project will use a large collection of non-Saccharomyces yeasts that have been collected from several Australian fermentative niches. These include samples of bee bread, stingless and sugarbag bees, floral nectar, and homogenized whole insects or insect guts. The yeast will be screened for novel enzymatic activities and assessed for their potential industrial use in fermented beverages.

Project available for: PhD students

Further information about the Alliance and the Joint PhD scheme can be found here: Jointly awarded PhDs with the University of Nottingham

Root growth angle (RGA) is an important trait that enables resource acquisition from different soil layers (e.g. steeper roots to access water deeper in soil profiles). Understanding RGA regulation and modifying RGA is one approach to adapt crops to climate change. We recently identified a novel gene, ENHANCED GRAVITROPISM1 (EGT1), controlling RGA in barley.

In this project, we will use a range of advanced gene editing and phenotyping technologies, including CrispR and X-ray imaging, to engineer and profile diversity for RGA in Australian barley germplasm and cropping environments, with the aim to engineer climate resilient Australian barley.

Project available for: PhD students

Further information about the Alliance and the Joint PhD scheme can be found here: Jointly awarded PhDs with the University of Nottingham

The ability of yeast to sense environmental changes and respond by altering morphology, such as the formation of filaments, which can become adhesive and invade penetrable surfaces is well known. However the mechanisms and triggers to this behavior, in particular arising from the cell population (cell chatter) have only been partially described.

We are interested to further this knowledge, by examining if cell-cell signaling molecules, particularly those triggered by nutrient status link mechanisms that may regulate and enable filamentation, such as mechanosensing. This project will contribute to the fundamental understanding of cell-cell signalling and the morphological result of such messages.

Project available for: PhD students

Further information about the Alliance and the Joint PhD scheme can be found here: Jointly awarded PhDs with the University of Nottingham

Salinity significantly reduces plant yield. In Australia the cost of salinity on agriculture productivity is valued at $1 billion pa. Efforts to improve crop salt tolerance have focused on limiting the delivery of toxic sodium (Na+) ions to leaves. Reducing Na+ in leaves has had a limited success in increasing crop salt tolerance. We hypothesis Na+ has an important role in lowering leaf water potential and enhancing water uptake in the dry Australian climate.

This project will establish the role of a key protein controlling Na+ transport to the shoot in driving salt tolerance in well-watered and water limited environments.

Project available for: PhD students

Further information about the Alliance and the Joint PhD scheme can be found here: Jointly awarded PhDs with the University of Nottingham

Soil compaction inhibits plant root penetration and water/nutrient uptake, reducing crop yields by 25%, and when combined with drought by up to 75%. Our recent work has shown that mechanical impedance is not the major driver of reduced root growth in compacted soils; rather, the hormone ethylene, released by the plant, limits root growth in compacted soils. This project will reveal the signalling pathway of ethylene-medidated plant response in response to compacted soil.

Project available for: PhD students

Further information about the Alliance and the Joint PhD scheme can be found here: Jointly awarded PhDs with the University of Nottingham

Due to climate change, drought is expected to increase this century, reducing the availability of arable land for food crops. Barley is the fourth most important cereal crop worldwide in terms of production, contributing £20B and $2.3B to the UK and Australian economy, respectively.

For plants to adapt to drought, roots must exhibit the ability to alter their root system architecture. The ability of roots to grow towards water, termed hydrotropism, is an important adaptation for enhancing water uptake in drying soil. Hydrotropism has been reported in several plant species, however there is limited information in crops.

The proposed project will aim to examine the hydrotropic root response using barley as a model crop species, potentially leading to crops better adapted to drought.

Project available for: PhD students

Further information about the Alliance and the Joint PhD scheme can be found here: Jointly awarded PhDs with the University of Nottingham

The Australian almond industry is increasing the use of organic amendments such as compost in their orchards to improve productivity and soil health. They are also investigating whole orchard recycling; where all the trees in the orchard are ground into chips and incorporated into the soil as part of orchard redevelopment. This project will monitor tree yield and soil organic matter to better understand the impact of these practices on orchard productivity and carbon sequestration.It will use lifecycle analysis to quantify the environmental impacts with an aim of improving the sustainability of Australian almond production.

Project available for: PhD students

Further information about the Alliance and the Joint PhD scheme can be found here: Jointly awarded PhDs with the University of Nottingham

National and commercial organisations around the world are pivoting towards the opportunity to develop a new hydrogen energy infrastructure and fill links in the supply-to-use value chain. Large-scale distributed storage reserves will be a key to smoothing out the variations in supply versus demand over time. Subsurface geological storage of natural gas currently achieves this on a seasonal basis for major population centres around the world.

In this PhD project, we intend to develop multiscale and multiphysics simulation models that consider the physiochemical property of hydrogen, hysteresis and its geochemical and microbiological interaction with rock and existing reservoir fluids. The model together with robust optimization algorithms will be used to assist with selecting and preparing prospective sites and managing storage systems that often involve frequent injection/withdrawal cycles while considering integrity and geological and phenomenological uncertainty. The developed package will be tested against a number of potential project scenarios, provided by the sponsor, Woodside Energy.

Project available for: PhD students

Taking inspiration from nature, this project will investigate textured surfaces for reducing drag on aircraft and ships using advanced experimental methods.

Project available for: PhD students

Using analytical models, porous surfaces will be designed and tested in wind tunnel experiments.

Project available for: PhD students

This project will investigate the effect of geometric parameters of surface perforations on turbulent drag.

Project available for: PhD students

Advanced experimental methods and numerical modellings will be conducted for this study.

Project available for: PhD students

This project will investigate the wind patterns over barley farms to develop an understanding of the effect of wind variations on head loss and lodging of plants.

Project available for: Mphil and PhD students

This project involves the design and silicone casting of different models of the blocked artery models and measuring the pressure drop inside them using the available coronary arterial test rig at the micro-fluidics lab.

The aim of the project is to understand the effect of blockage inside the coronary arteries on heart performance. The outcome of this research will help cardiologists to better understand the underlying mechanisms for coronary artery diseases and will help biomechanical engineers to design more personalised and accurate coronary artery assist devices (CAAD).

Project available for: Mphil and PhD students

This project will investigate the mechanical properties of different varieties of barleys and the effect of genetic modification on their mechanical properties with the aim to reduce the head loss in collaboration with the school of Agriculture Food and Wine.

Project available for: Mphil and PhD students

However, the process development is still very labour intensive and poorly automated.

This project aims to investigate automated model-based control of chromatography applying AI and mechanistic modelling approaches. An ideal candidate has already some experience in programming and enjoys the challenge of a cross disciplinary, highly applicable field.

Project available for: Mphil and PhD students

A challenge is the production of functional proteins that can substitute animal derived proteins in a variety of vegan food products. These proteins can be produced in yeast in a process often called precision fermentation.

The aim of this project is to investigate the large scale production of milk proteins applying continuous fermentation and purification methods.

Project available for: Mphil and PhD students

Climate change stressors such as warming and acidification of the oceans are predicted to have dramatic impacts on the diversity, abundance, and distribution of fish species worldwide.

The degree to which fishes adapt to or tolerate changing conditions will determine their persistence in their original habitats as well as their ability to extend their ranges to novel habitats or higher latitudes.

My research focuses on the effects of global change and human impacts on aquatic species and ecosystems. The studies are highly relevant for management purposes and to understand how climate change will affect productivity and resilience of coastal ecosystems and their associated animal populations.

Project available for: Mphil and PhD students

Natural volcanic CO2 vents at New Zealand or Japan are the primary area from which fish samples are obtained for analysis in this project.

Climate change stressors such as warming and acidification of the oceans are predicted to have dramatic impacts on the diversity, abundance, and distribution of fish species worldwide.

The degree to which fishes adapt to or tolerate changing conditions will determine their persistence in their original habitats as well as their ability to extend their ranges to novel habitats or higher latitudes.

My research focuses on the effects of global change and human impacts on aquatic species and ecosystems. The studies are highly relevant for management purposes and to understand how climate change will affect productivity and resilience of coastal ecosystems and their associated animal populations.

Project available for: Mphil and PhD students

Mangroves are common (sub)tropical plant species that live in coastal intertidal zones. As a result of climate change they are extending their distribution ranges to higher latitudes and invading temperate coastal salt marsh habitats. Mangroves and salt marshes both act as important nursery and feeding areas for a wide range of species, including fishes, shrimp, crabs, and birds.

South Australia represents a temperature mixing zone where mangroves and salt marshes co-occur, and where climate transitions from subtropical to temperate. With ongoing global warming it is expected that the mangroves will move southwards, but it is unknown if their associated fish communities will show a similar response and how these fishes will be impacted by increasing temperature and other global stressors.

Field studies will reveal the fish abundance, biodiversity and community composition in mangroves across their current distribution in South Australia. Video recordings will be taken to study fish behaviour. Fishes will also be collected to study their condition and fitness. Within this broader theme, there will be a range of projects for students to choose from.

The information gained will be valuable to predict future nursery function and habitat importance of mangroves for fishes in South Australia, how this might affect current marine protected areas, and which fish species will be the local winners or losers of climate change.

Project available for: Mphil and PhD students

The student will gain interdisciplinary research experience at the intersection of biomedical engineering and neuroscience.  

Project available for: Mphil and PhD students

The student will gain interdisciplinary research experience at the intersection of biomedical engineering, computer science, cardiology and neuroscience.    

Project available for: Mphil and PhD students

Project available for: Mphil and PhD students

You will use CRISPR genome editing to precisely modify the vetch (legume) genome, use whole genome sequencing to confirm the genome integrity and measure the abundance of the deleterious amino acids using LC-MS.

Number of students: 1

Project available for: Mphil and PhD students

The project will involve use of biochemical techniques to assay the function and genetic complementation of the Bacillus mutant.

Number of students: 1

Project available for: Mphil and PhD students

The input power used in these applications can be coming from a wide range of sources such as solar panel, stored energy or fuel cell. The aim of this project is to develop a programmable integrated power management module using wide bandgap-based devices with specification that be fine tuned to wide range of application.

Project available for: Mphil and PhD students

Introduction of disease-causing mutations into animal models using genome editing techniques provides a way around this problem. We combine this strategy with advanced multi-omics and bioinformatic analyses to investigate the initiating causes of Alzheimer's disease. Childhood dementia (e.g. Sanfilippo syndrome) has relatively simple genetic origins and may be an extreme, very early form of Alzheimer's disease, so analysing it may reveal therapeutic approaches to both forms of dementia.

Project available for: Mphil and PhD students

Yet, one major obstacle prevents AI from being adopted equitably. At present, most AI models and systems are developed with many oversimplified assumptions while ignoring a wide range of real-world factors that might render such "lab-grown" AI unusable when deployed to certain populations. This project will investigate equitable AI for knowledge workers: how and why existing AI behaves inequitably and how to design multi-stakeholder computing systems to troubleshoot inequitable AI . We will focus our scope on AI-assisted disease screening and diagnosis, including colonoscopy, ultrasound, and long COVID tracking.

Project available for: Mphil and PhD students

The hybrid integration technologies will enable the integration of photonics technologies on emerging electronics platforms, new devices enabled by such integration of different material platforms, and integration of semiconductors on non-traditional substrates (including flexible platforms). These applications enabled by this new direction include advanced sensors for internet-of-things systems and heterogeneous integration technologies for health-sciences. The applications areas include medical imaging, implantable medical devices, and wearable systems. Students with backgrounds in Electrical and Electronic Engineering, Biomedical Engineering, Materials Engineering, Mechanical Engineering, or Quantum Engineering will be highly appropriate for this project.

Project available for: Mphil and PhD students

The lack of room-temperature semiconductor solution has been the limiting factor in the progress of terahertz systems. The project will focus on the pursuit of semiconductor materials innovations, nanoscale device design, quantum computational methods, and circuit-level implementations of the quantum-based structures to create room-temperature terahertz sources. Students with backgrounds in Electrical and Electronic Engineering, Physics, Materials Engineering, Mechanical Engineering, or Quantum Engineering will be highly appropriate for this project.  

Project available for: Mphil and PhD students

The lack of room-temperature semiconductor solution has been the limiting factor in the progress of terahertz systems. The project will focus on the pursuit of semiconductor materials innovations, nanoscale device design, quantum computational methods, and circuit-level implementations of the quantum-based structures to create room-temperature terahertz sources. Students with backgrounds in Electrical and Electronic Engineering, Physics, Materials Engineering, Mechanical Engineering, or Quantum Engineering will be highly appropriate for this project.  

Project available for: Mphil and PhD students

This project aims the pursuit the discovery of biomedical properties of biological materials enabled under sub-femtosecond (or attosecond) pulse lasers, and new semiconductor manufacturing by using the large power density enabled by these ultrashort pulsed lasers. Students with backgrounds in Electrical and Electronic Engineering, Physics, Materials Engineering, Mechanical Engineering, or Quantum Engineering will be highly appropriate for this project. 

Project available for: Mphil and PhD students

The project aims to advance the frontiers of ultrawide bandgap semiconductors - in the material design, epitaxy, and fabrication - to form nanoscale, materials, devices, and circuits that will push the power conversion efficiency in light-emitting diodes for microdisplays, diode lasers, power electronics, integrated circuits for biomedical and sensors applications, and micro/nano-electromechanical systems (MEMS/NEMS). This project will bring the students to work in a combined experimental and computational environment. The materials will include group III-nitrides, III-oxides, and III-oxynitride semiconductors. Students with backgrounds in Electrical and Electronic Engineering, Physics, Materials Engineering, Mechanical Engineering, Computer/Mathematical Sciences, or Quantum Engineering will be highly appropriate for this project. 

Project available for: Mphil and PhD students

This project aims at inverse designing complex photonics, electronics, and nanoscale devices by using applied machine learning and artificial intelligence engineering. This project will marry physical electronics (semiconductor technologies) and artificial intelligence in addressing some of the most complex technologies for microdisplays, optical coherence tomography (biomedical engineering), space electronics, electric vehicles (power electronics), and defence (high-power lasers). Students with backgrounds in Electrical and Electronic Engineering, Physics, Materials Engineering, Mechanical Engineering, Computer/Mathematical Sciences, or Quantum Engineering will be highly appropriate for this project.

Specifically, the use of machine learning technique will be used to answer the questions on:
i) how the system-level properties will be used as the “guiding principles” for the right nanodevices and materials,
ii) how the machine learning in the device and material innovations will lead to advances in computational techniques,
iii) how the synthesis and structures materials for specific target properties can be achieved,
iv) how the specific mechanical, electrical, thermal, and optoelectronics properties for certain applications can drive the requirement for the new material compositions and nano / interfacial structures, and
v) how the nanocomposite structures will provide specific properties as defined from applications.

Project available for: Mphil and PhD students

 Students will work on materials, devices, characterizations, and computational design of state-of-the-art laser devices. Students will develop capabilities in using molecular beam epitaxy, micro/nanofabrication facility, and advanced characterization tools for semiconductors technologies. Students with backgrounds in Electrical and Electronic Engineering, Physics, Chemical Engineering, Materials Engineering, Mechanical Engineering, or Quantum Engineering will be highly appropriate for this project. 

Project available for: Mphil and PhD students

Development of new diagnosing methods is also a part of this HDR project, which is training next-generation Australia scientists in advanced laser diagnostics and supporting the development of an Australia-based carbon capture technology in heavy industries.

Project available for: Mphil and PhD students

This HDR project is also aimed to educate and train next-generation scientists in advanced laser diagnostics and renewable energy.

Both experiments using advanced laser diagnostics and computational fluid dynamics (CFD) modellings are involved, providing an unique training opportunity for new-generation scientists.

In particular, we are able to analyse at far greater spatial scale and with greater precision than a decade ago. An opportunity is presented where Cu and Zn isotopes can be applied to mineralised rocks in order to track the potential source(s) and direction of fluids in the system. Thus far, previous studies have focussed on Cu porphyry systems while IOCGs have not been the subject of a major study, probably due to their complexity and the potential for large data scatter. Improved precision means that we are now at a point where a spatially constrained study of a well-characterised deposit like Olympic Dam can reveal fundamental information on how metal isotopes vary across distinct zones of mineralisation and may reveal insights into the primary sources of copper mineralization at Olympic Dam and other IOCG deposits in the Olympic Cu-Au province. The isotope data may also show whether in the future they can be used as vectoring tools.

Project available for: PhD students

A continuous-flow process will be developed for the precipitation of a leached solution of metal-containing waste, from electronic boards to spent lithium-ion batteries. The aim is to unlock the potential for efficiency in downstream of the secondary critical mineral production by separate and purify critical metal resources, such as Co(II) oxalate, which is used in the preparation of cobalt catalysts, clean energy technologies and cobalt metal powder for powder-metallurgical applications. Potential innovation levers are tailored solvents, including deep eutectic solvents (DES); selective precipitation agents, including ammonium oxalate; advanced mixing and processing equipped, including StoliChem's multistage continuous stirred reactor and coiled inverted-flow (CFI) reactor. Those experiments in Adelaide will be complemented by advanced process equipment in Nottingham, including a spinning-disk reactor and temperature-gradient segmented-flow reactor as well as advanced analytical characterization in real-time and in-line, for example amplifying x-ray structural analysis by use a synchrotron beam.

Project available for: PhD students

Further information about the Alliance and the Joint PhD scheme can be found here: Jointly awarded PhDs with the University of Nottingham

Access to daylight, the quantity as well as quality of daylight, have been shown to impact occupant satisfaction with their indoor environment, which may also contribute to their wellbeing. This research investigates the impact of daylight on older people and to what extent that the absence or not having sufficient amount of daylight affects their wellbeing. The research will benefit building designers and developers of housing for older people including private and public housing, retirement homes and aged care facilities. The research will be conducted through field study in Adelaide, followed by further investigation using Virtual Reality and daylight simulation in the daylighting lab at University of Nottingham.

Project available for: PhD students

Further information about the Alliance and the Joint PhD scheme can be found here: Jointly awarded PhDs with the University of Nottingham

Furthermore, seafood provenance is often prone to uncertainty due to mislabelling of imported products or illegal fishing practices. This PhD project will aim to develop an innovative toolkit to quantify and assess the links between seafood provenance (e.g., through stable isotope analysis) and quality (e.g., omega-3 fatty acids, contaminants, microplastics). By blending biochemical analysis using mass spectroscopy with spatial ecological modelling, this project will inform environmental and fisheries management towards improved seafood quality and promotion of local seafood products.

This project will offer opportunities for field and lab work, and a close collaboration with Australian industry and government partners. Key study species could include (but are not limited to) barramundi, garfish, prawns, snapper and oysters. Priority will be given to candidates with previous lab work experience and strong quantitative skills.

Project available for: PhD and MPhil students

The mycorrhizal pathway of phosphorus uptake is important for plants, but may lead to increased accumulation of the anti-nutrient compound phytate in grains and pulses. This project will uncover how mycorrhizal fungi affect phytate accumulation in the edible portion of crops, and how this modifies the bioavailability of micronutrients such as zinc and iron for human consumption. The PhD candidate will inoculate plants with mycorrhizal fungi and grow them until maturity. The resulting grain samples will be analysed for bioavailability and bioaccessibility of Zn and Fe.

The project will include the following experimental work: plant physiology and nutrition, soil biology, assays for bioavailability of micronutrients in plants, molecular biology (if of interest).

Phosphorus fertiliser is an expensive input in macadamia production, but beneficial soil microbes such as mycorrhizal fungi that take up phosphorus and other nutrients into macadamia plants, can potentially bridge the gap with reduced fertiliser inputs. This project will leverage beneficial soil microbes and root traits to improve phosphorus uptake efficiency to optimise phosphorus fertiliser management in a sustainable manner.

The project will include the following experimental work: root phenotyping using CT scanning, isotope tracing, plant physiology and nutrition, microscopy.

Reducing carbon emissions from the built environment is to achieve zero carbon emissions by 2050. Since 85% of existing buildings are expected to still be standing by 2050, cost-effective retrofitting of the existing stock is important to meet these targets. An accurate in-situ characterisation of the fabric of existing buildings is necessary to design effective retrofit measures. However, current techniques rely on one-dimensional assumptions that do not account for the presence of thermal bridges. These substantially decrease the thermal efficiency of buildings and lead to moisture condensation, affecting indoor air quality.

Using infrared thermography this project aims to develop a new methodology to characterise the thermophysical properties of buildings' fabric and account for these effects in the simulations of buildings' energy performance.

The contribution of PV energy to the electricity generation mix continues to grow. Accelerating the adoption of solar energy will present significant challenges to the electricity transmission and distribution system, as solar power is not dispatchable and therefore its incorporation as a major element of the generation mix requires the accurate prediction of solar energy production.

To tackle this issue, this project is going to significantly improve the prediction accuracy for intra-hour solar forecasting by developing and demonstrating a solar measurement (e.g. ground- based sky images) and modelling platform to support multiple data sources and intensive prediction algorithms.

This project looks at improving the prediction of wildfire likelihood using remote sensing (RS) and paleoclimatic reconstruction (PR) approaches.

Established on the collaboration between UoA and UoN, this project aims to replace the conventional data sets with RS and PR data sets, and test the performance of fire prediction model, with case study in Australia and Italy. This joint project will showcase how the process of predicting future wildfires can be automated and enhanced with higher precision.

To tackle this issue, this project is going to significantly improve the prediction accuracy for intra-hour solar forecasting by developing and demonstrating a solar measurement (e.g. ground- based sky images) and modelling platform to support multiple data sources and intensive prediction algorithms.

During summer, trees provide shades and evapotranspiration, reducing urban heat island effect and heat gain in buildings and improving thermal comfort. However, these same trees could affect solar photovoltaics (PV) performance by shading them, resulting in less electricity generated.Both Australia and UK encourage increasing tree canopy cover as well as solar PV installations, for example, as stated in the 30-Year Plan for Greater Adelaide and the UK’s goal to increase PV installations from 13.4 GW in 2020 to 40 GW by 2030. These goals present a dilemma: do we want more tree canopy cover or more solar-generated electricity in our future cities? Is there an optimal greenery-solar integrated development strategy that utilises the cooling effect of urban greenery without compromising solar PV efficiency? This project investigates the relationships between solar panel performance, indoor and outdoor thermal comfort, and urban greenery.

Despite Australia’s potential as a solar superpower, the nation lags behind in research and development of agrivolatics suited to our warm and dry conditions. This project aims to optimise a vitivoltaics system suited to vineyards and investigate light impacts on photosynthesis, grapevine shading, grape berry chemistry, canopy management, and water use management of grapevines, under the types of shading imposed by overhead photovoltaic systems. Our University of Nottingham partners are international leaders in understanding how plants respond to transitory shading and temperature, thereby bringing needed IP to the project.

Agrivoltaics is becoming a hot research topic internationally and offers a "win-win" system to mitigate impacts of climate change on horticulture systems while simultaneously generating electricity. Poorly structured soils are a major cause of reduced productivity in global agriculture, with about two-thirds of the world's soils being degraded. Additionally, they contribute to a range of negative environmental impacts. Current management responses typically involve repeated applications of ameliorants, which have limited and short-lived effectiveness due to their inability to influence subsoils. To address this issue, we propose a novel strategy based on "re-engineering the rhizosphere," which aims to advance our fundamental understanding of the biogeochemical processes that regulate soil organic carbon stabilization in the zone of soil-plant-microbe interaction responsible for carbon and nutrient cycling. This project employs an innovative combination of advanced X-ray Computed Tomography (CT) and sophisticated metagenomics-isotopic approaches to unravel important interactions between carbon geochemistry and the iron cycle in soils. These new data will inform rhizosphere engineering strategies to bolster crop nutrient use efficiency and agricultural productivity. They will also help reveal the complex soil-based interactions underlying the carbon cost of agriculture due to rhizosphere processes. By bridging the research fields of soil science, environmental biogeochemistry, microbial metagenomics, crop physiology, and chemical engineering, this interdisciplinary project aims to engineer a rhizosphere with increasing sophistication to enhance the efficiency and sustainability of crop production.

Innovations in the biosciences through advances in gene-editing and synthetic biology are presenting exciting opportunities for tackling some societal grand challenges. However, these technologies also raise several ethical questions including weighing risks and benefits, impact on human-nature relations, sustainability implications, public and stakeholder engagement in biotechnology development, nature of ownership and access to biotechnology, to name a few. In order to support innovation and excellence in agricultural research there is a need to develop a responsible research and inclusive innovation (RRII) approach. This project will be involved in developing a practical approach for training researchers in agriculture in RRII approaches.

Modern artificial intelligence (AI) methods have achieved excellent performance in a variety of healthcare applications, including but not limited to treatment planning, disease diagnosis, treatment response prediction, etc. To increase the intelligence level and performance of AI solutions in these clinical areas, it becomes crucial to comprehensively collect, understand, interpret, and integrate information from multiple sources (e.g. imaging, clinical record, text, etc.).

This project aims to develop novel AI solutions that utilise multimodal information to improve diagnostic accuracy, efficiency and reliability in real clinical practice settings.

Mushrooms hailed as the world's most sustainable crop, encounter a pressing issue of freshness maintenance, leading to a substantial 30% waste in small and medium-scale cultivation. Furthermore, the flavour of mushrooms significantly impacts the revenue of producers. This PhD project aims to address these challenges by developing AI-based solutions that automate the optimization of the cultivation environment, monitor mushroom growth, and predict flavour generation. Leveraging the industry partner's semi-smart system, the research and development will undergo evaluation on their farm, ensuring practical applicability.

This project is offered through the Joint PhD scheme of the Adelaide-Nottingham Alliance, a strategic initiative of the University of Adelaide and the University of Nottingham.

Bixlozone is a new to market herbicide for grass weed control in a variety of crops. However, despite no prior exposure, we already have weeds with resistance to bixlozone.

This project aims to obtain a better understanding of how this resistance has evolved. The project will investigate the potential involvement of cytochrome P450s, utilising qPCR and western blotting to investigate gene and protein expression, and metabolomic studies to look at herbicide fate.

Project available for: PhD and MPhil students

Experimental analysis of air quality will be conducted before and after the installation of cookstove strategies, including use of new stoves, different fuels, and other strategies. There is scope for multiple students.

Project available for: PhD and MPhil students

Analysis of the logistical aspects of camps will be conducted to establish base-line resource circularity, with the development of models to then optimse the establishment, operations, and end-of-life aspects of refugee and IDP camps. There is scope for two students.

Project available for: PhD and MPhil students

The application of the existing DRR frameworks will be tested to the application in order to determine suitability and potention modification/optimisation.

Project available for: PhD and MPhil students

GIS will be used to determine localised suitability for renewable energy options. Techno-economic analysis will be conducted for suitable energy solutions. Verification can be conducted from extant systems of various scales and generation types.

Project available for: PhD and MPhil students

Case studies on the teaching of communities in Pacific Islands how to design, size, install, maintain, and operate pico-hydropower systems will be used.

Project available for: PhD and MPhil students

Experimental and numerical analysis will be conducted to understand the process in order to optimse systems for resource-constrained communities.

Project available for: PhD and MPhil students

The work is experimental and conducted across engineering and science. There is scope for multiple students.

Project available for: PhD and MPhil students

Project available for: MPhil students