Scholarships

The Australian Institute for Machine Learning is recognised as one of the top artificial intelligence (AI) and machine learning research institutions globally. We are pleased to offer funding and scholarship opportunities for prospective students. Please see below for a current list of scholarships.

Industrial AI Program Scholarships

We are pleased to offer Industrial AI Program Scholarships for students undertaking their honours or higher degree by research (HDR) studies in AI and machine learning. Funded by the state government, these scholarships are available for honours, master's and PhD students.

For more information on each of these scholarships, including eligibility and application details, refer to these pages:

Undergraduate scholarships

Postgraduate scholarships

Applicants must be citizens of Australia, the United Kingdom, or the United States of America, or Australian permanent residents who are acceptable for candidacy for their relevant degree at the University of Adelaide.

Industrial AI Program Scholarships at PhD level include travel funding to gain valuable experience working with international collaborators in the United Kingdom or the United States of America.

 

Industrial AI PhD Scholarship key points

 

AIML Research Scholarships

The AIML Research Scholarships support exceptional students engaged in advanced research in AI and machine learning. These scholarships are available for students undertaking their honours and postgraduate by coursework degrees.

For more information on each of these scholarships, including eligibility and application details, refer to these pages:

Applicants must be citizens or permanent residents of Australia, citizens of New Zealand, permanent humanitarian visa holders or international students.

Applicants are invited to propose a research project and AIML supervisor of their choice, or select from this list of supervisors and available projects:

Dr Dhani Dharmaprani
  • Development of novel calibration methods for cardiac digital twins
  • Correlation between invasive and non-invasive cardiac mapping
Dr Anh-Dzung Doan and Professor Tat-Jun Chin
  • Time domain adaptation in visual perception using Grand Theft Auto V data
Dr Feras Dayoub
  • Object detection for mobile robots
  • Autonomous inventory management using robotic systems
Associate Professor Lingqiao Liu
  • Leveraging AI for educational material generation: transforming documents into slides with large language models
  • Optimising 3D bin packing with machine learning (sponsored by industry partner Gale Pacific Ltd)
Dr Marcus Martens
  • Analysis of simulated spacecraft fragmentation using neuromorphic vision
Professor Minh Hoai Nguyen
  • 360Gaze: revolutionising eye tracking with immersive vision
Dr Wei Zhang
  • Constructing knowledge graphs from clinical guidelines
Dr Henry Li
  • Generative machine learning models for accelerating CO2-capture material discovery
Dr Jinan Zou
  • Large language model (LLM) for AI education
Dr Xinyu Wang
  • Exploring the social attributes of large language models
Dr Qi Chen
  • Advance multimodal large language models' capacity of understanding, reasoning, and generation
Dr Zhibin Liao
  • Automated detection and tracking of marker particles in videos for diagnosing cystic fibrosis

Hear from our students

Joytu Khisha is a recipient of an AIML Research Scholarship and is undertaking his master's studies with the Embodied AI and Robotic Vision Research Group led by Dr Feras Dayoub. In this interview, Joytu shares his innovative research in mimicking of human movements and how this project has enabled him to fulfil his career aspirations.

 

Other scholarships

The University of Adelaide offers a range of scholarships to undergraduate and postgraduate students. These scholarships, as well as many others funded by industry and non-profit organisations, are available to potential and currently enrolled students.

University Scholarships

The University offers a wide range of PhD scholarships for incoming students. A full list for scholarships is available here.