Description

SCHOLARSHIPS

The Australian Institute for Machine Learning is recognised as one of the top artificial intelligence and computer vision research institutions globally.

Our new Centre for Augmented Reasoning scholarships are funded by the Department of Education, Skills and Employment to support full-time PhD students who are commencing research in machine learning with a focus on augmented reasoning.

Eligibility

Applicants must be Australian citizens or permanent residents of Australia; or international students who are acceptable as candidates for a PhD degree at the University of Adelaide. Female applicants are strongly encouraged to apply.

Scholarships

There are nine (9) scholarships available, to be paid at a rate of AU$40,000 per annum. They are likely to be tax exempt, subject to Australian Taxation Office approval.

They include: 

• Five (5) standard three-year scholarships, with possible 6 month extension
• Four (4) four-year scholarships available to suitable applicants to encourage female applicants and those from other disciplines

Additional information

For further information specific to each research project, please contact the principal supervisor identified below. For general information, contact Dr Angela Noack, Program Manager, Centre for Augmented Reasoning, Australian Institute for Machine Learning (AIML).

Research projects

Expand

• Next Generation Causality

• Reasoning in Vision-and-Language: Close the Gap Between Machine and Human

  Area of research	Project title	Project description	Lead researcher
  School of Computer Science	Reasoning in Vision-and-Language: Close the Gap Between Machine and Human	2 x PhD scholarships AU$40,000 per annum In this project you will research and develop novel algorithms that can ground vision language to real-world daily applications. This research project in Computer Vision, Visual Question Answering, and Vision-and-Language technology more broadly is developing and exploring 5 research themes: Integrating prior knowledge into vision-and-language with symbolic reasoning Explainable Visual Question Answering Vision-and-Language in the wild: causality, reliability and generalisability Fine-grained control of image2text and text2image generation Human-centred Vision-and-Language Navigation. This Scholarship is within CAR RESEARCH THEME 2: Interactive Machine Learning. This is a standard 3-year scholarship with a possible 4-year scholarship available to suitable applicants to encourage students from other disciplines, especially women, who wish to undertake additional training in machine learning methods. To find out more contact Dr Qi Wu at the Australian Institute for Machine Learning (AIML) to discuss.	Dr Qi Wu

   

• Understanding Bias Caused by User Interaction with AI in High-Risk Decision Making

  Area of research	Project title	Project description	Lead researcher
  Neuroscience, Behaviour and Brain Health	Understanding Bias Caused by User Interaction with AI in High-Risk Decision Making	PhD scholarship AU$40,000 per annum In this project we aim to understand the sources of bias created by AI/human interactions in AI supported high-risk decision making, and to define safe methods for AI systems to present their outputs to human users. This Scholarship is within CAR RESEARCH THEME 2: Interactive Machine Learning. This is a standard 3-year scholarship with a possible 4-year scholarship available to suitable applicants to encourage students from other disciplines, especially women, who wish to undertake additional training in machine learning methods. To find out more contact Dr Luke Oakden-Rayner at the Australian Institute for Machine Learning (AIML) to discuss.	Dr Luke Oakden-Rayner

   

• Semantically Meaningful Deep Learning Abnormality Prediction Model

  Area of research	Project title	Project description	Lead researcher
  School of Computer Science	Semantically Meaningful Deep Learning Abnormality Prediction Model	PhD scholarship AU$40,000 per annum In this project we aim to build more robust and explainable abnormality prediction models. 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 explainability about the prediction. 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. This Scholarship is within CAR RESEARCH THEME 4: Machine Learning Driven Science Discovery. This is a standard 3-year scholarship with a possible 4-year scholarship available to suitable applicants to encourage students from other disciplines, especially women, who wish to undertake additional training in machine learning methods. To find out more contact Dr Gabriel Maicas at the Australian Institute for Machine Learning (AIML) to discuss.	Dr Gabriel Maicas

   

• Building Causal Models for Predicting Treatment Outcome in Patients - Towards the Automated Bioinformatician

  Area of research	Project title	Project description	Lead researcher
  School of Computer Science	Building Causal Models for Predicting Treatment Outcome in Patients - Towards the Automated Bioinformatician	PhD scholarship AU$40,000 per annum Deep Learning has had significant interest in a multitude of medical applications. There is an increased interest in learning more explainable models, including causal models. In this project 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. This Scholarship is within CAR RESEARCH THEME 4:Machine Learning-Driven Science Discovery. This is a standard 3-year scholarship with a possible 4-year scholarship available to suitable applicants to encourage students from other disciplines, especially women, who wish to undertake additional training in machine learning methods. To find out more contact Dr Johan Verjans and Professor Javen Shi at the Australian Institute for Machine Learning (AIML) to discuss.	Dr Johan Verjans

• Scalable Compositional Semantic Meaning Representation and Reasoning

  Area of research	Project title	Project description	Lead researcher
  School of Computer Science	Scalable Compositional Semantic Meaning Representation and Reasoning	PhD scholarship AU$40,000 per annum In this project we aim to develop novel semantic representations for natural languages.   Specifically, we aim to develop natural language understanding methods that can generalise across scenarios and support complex reasoning. This Scholarship is within CAR RESEARCH THEME 3: Knowledge, Representation and Generalisation. This is a standard 3-year scholarship with a possible 4-year scholarship available to suitable applicants to encourage students from other disciplines, especially women, who wish to undertake additional training in machine learning methods. To find out more contact Dr Lingqiao Liu at Australian Institute for Machine Learning (AIML) to discuss.	Dr Lingqiao Liu

   

• Towards "Small Data, Big Problem" Learning and Reasoning Paradigms

  Area of research	Project title	Project description	Lead researcher
  School of Computer Science	Towards "Small Data, Big Problem" Learning and Reasoning Paradigms	PhD scholarship AU$40,000 per annum In this project at the new Centre for Augmented Reasoning we aim to develop novel machine learning and reasoning paradigms.   Specifically, we want to develop solutions for "small data, big problem" scenarios, with the focus on improving the generalisability of machine learning systems across domains and tasks. This Scholarship is within CAR RESEARCH THEME 3: Knowledge, Representation and Generalisation. This is a standard 3-year scholarship with a possible 4-year scholarship available to suitable applicants to encourage students from other disciplines, especially women, who wish to undertake additional training in machine learning methods. To find out more contact Dr Lingqiao Liu at Australian Institute for Machine Learning (AIML) to discuss.	Dr Lingqiao Liu

   

• Theory of Mind in AI and ML

How to apply

Expressions of interest should be submitted to Ms Lina Court with the name of scholarship in the subject heading, no than 30 November 2021. Please ensure you include all of the following documents: 

• A completed Expression of Interest Form 
• Evidence of Australian or New Zealand citizenship, or Australian permanent resident status (if applicable)
• Academic transcripts
• Translations of non-English documentation
• Curriculum vitae

If successful, an academic will guide you to submit a formal application using the Adelaide Graduate Centre online system.