PhD Scholarships in AI/ML

The Applied Artificial Intelligence Institute (A2I2) at Deakin University, Australia currently offers multiple full 3-year PhD scholarships to study AI/ML.

Research areas
Selection criteria
What to send

Research areas

AI Future

We build learning intelligent systems that are general, competent, energy-efficient and human-compatible. Areas of interest are:

> Agents as Digital Species presents the concept that an agent has lifewide experience to interact and work with other agents and humans, evolving lifelong with the dynamics of its environments. Equipped with perception, memory, statistical relational learning, theory of mind, common sense, knowledge and reasoning capabilities, we aim to bring this new digital species to a new level.

We will invent new kinds of machine learning, explore novel forms of computation and learning to improve lifelong adaptation with small energy footprints. This includes, but is not limited to, small-but-powerful language/foundation models, learning to explore, human-in-the-loop, self-supervised learning, knowledge-guided learning, prompt optimisation, distillation, continual learning, novelty seeking, intrinsic motivation, and physics-informed ML.

> System 2 Capability focuses on finding efficient ways for learning to reason with minimal human supervision and solving complex problems that require deliberate thinking. Our sub-areas include, but are not limited to: causal inference, systematic generalisation, graph neural networks, relational models, memory and attention, reasoning, and knowledge-guided learning to reason. 

> AI Alignment focuses on developing novel machine learning frameworks to incorporate human perspectives, sometimes implicit, into AI to mitigate negative impacts caused by unintended consequences if left unchecked. Expected outcomes include new frameworks for machines to rapidly learn from and reason about human preferences, and actively pursue benefits for humans as intended. Expected benefits are advanced capabilities for effective human-machine partnership, pushing the frontier of responsible AI.

AI Impact

We want to use AI to make the world better. Here are a few things we are passionate about:

Selection criteria

There is no single selection criterion and we can only say that we look for candidates who have potential to have a successful research career, not just a PhD degree. If you do not know what it takes for a research career, I recommend that you should spend time to read about it. Sometimes it will help you decide whether you need a PhD or not. Here is the list of things we are looking for:

• Thirst of conquering the unknowns and willing to pursue a research career. PhD is just a stepping stone, and a by-product of the learning process.
• Research experience (e.g. has published papers).
• Academic recognition: university prizes and awards. High quality honours at high school (such as members of national or international teams) may also count. 
• Bachelor/Master in CS/Maths/Physics with excellent academic performance from a well-recognised university. For those with Australian qualifications, the standard requirement is an Honours degree. 
• Good math background (we will use a lot of statistics, optimization and linear algebra).
• Good programming skills. An ability to scale up to large datasets is a bonus.
• Good machine learning & AI background. As a general rule of thumb, a good AI/ML PhD student will be likely to have covered statistical machine learning & probabilistic graphical models. A prior exposure to deep learning is a great bonus.
• Good English (generally IELTS score 6.5, no bands below 6, is required for entry, but you should be aware that this score is insufficient for smooth communication). Good critical reading skills are vital because you will spend up to 50% of your time for reading. Technical writing is also important because it is often the end-product for assessment, and it accounts for 50% chance of acceptance.

What to send

The rule of thumb is that you should send whatever (electronic) documents you think that will support your future research career. Documents are written in English and may include some of the following:

• A comprehensive resume (or CV);
• Academic transcripts;
• Theses;
• Published papers or technical reports (if written in languages other than English, titles and abstracts should be translated to English);
• A statement of purpose briefly describes your research intention and interests, general approach to reach your PhD/career goals;
• Proposal for the intended thesis; and
• Reference letters from your professors.

You can send your documents directly to Professor Truyen Tran.

Last updated: Oct 25th 2024