Grant-Funded Researcher (B), Scalability of Deep Learning, AIML

Adelaide, Australia
$102,952 to $121,779 per annum plus an employer contribution of up to 17% superannuation may apply
19 Jan 2023
End of advertisement period
05 Mar 2023
Contract Type
Fixed Term
Full Time

(Level B) $102,952 to $121,779 per annum plus an employer contribution of up to 17% superannuation may apply.

There is one 2-year fixed-term position available, with the possibility of an extension, subject to project end-date. Flexible work arrangements can be negotiated with the right candidate.

Be part of the Australian Institute for Machine Learning – the largest computer vision and machine learning research group in Australia and contribute to world leading Augmented Reasoning research projects.

AIML is Australia’s leading research institute in machine learning and artificial intelligence. AIML’s computer vision research is among the best in the world. With world-leading researchers, modern facilities and an innovative culture, we’re committed to delivering research that is highly valued by our local and global communities. Located at Lot Fourteen, Adelaide, AIML is the largest computer vision and machine learning group in Australia with more than 170 members including academics, research staff, and students.

The institute works on a mixture of fundamental and commercially oriented research projects in computer vision and machine learning. Find out more at

The Centre for Augmented Reasoning (CAR) is a $20M investment by the (then) Department of Education, Skills and Employment in people and research to make computers better at interacting with humans so that all technology is easier and safer to use. Managed under AIML, the Centre is supporting Advanced Reasoning research through grants and PhD scholarships, facilitating innovation and rapid commercialisation, and increasing artificial intelligence (AI) literacy and engagement in Australia.

The postdoctoral researcher for Scalability of Deep Learning will be supervised by Dr Yifan Liu. The role will contribute to the centre’s objective to build world-class research capability in machine learning (ML) while demonstrating the potential and impact of this knowledge for industries in Australia.

Scalability is a high-level problem in AI research that holds much promise. Large vision models with sufficient labelled data on a well-defined benchmark will lead to break-through performance in fundamental tasks and will help with downstream tasks. However, when applying these models to industry applications, many challenges remain, such as: adaptation to new classes and instances, efficiency on mobile devices, lack of labelled data, and convergence problems during fine tuning.

This postdoctoral role will investigate:

1. The scale of the data:

  • using semi-supervised learning, weakly supervised learning, and interactive labelling techniques under a more practical, real-world setting to increase the generalization ability of the model in 2D, 3D scene understanding and generation tasks.
  • designing unified structures for multi-tasks and multi-modality input to make use of existing labels in different tasks to scale up the training data.

2. Training efficiency:

  • Improving the training efficiency or reducing the trainable parameters when adapting vision foundation models to new tasks.

3. Specializing:

  • Developing efficient solutions for specializing a generalist for a local task 

To be successful you will need:

  1. A PhD in computer science or related discipline, or equivalent industry experience
  2. Programming experience and expertise in Python, or C++, or other relevant languages
  3. Experience and demonstrable expert knowledge in one or more of the following areas: multi-modal, multi-task, robust and intelligent perception
  4. Track record of publications in top-tier machine learning, computer vision, artificial intelligence and/or robotics conferences and/or journals, commensurate with experience and opportunity

Desirable characteristics:

  1. Has the experience and/or ability to contribute to the promotion of research capabilities to industry and the wider community
  2. Has familiarity with deep learning frameworks, e.g., PyTorch or TensorFlow.

Enjoy an outstanding career environment.

The University of Adelaide is a uniquely rewarding workplace. The size, breadth and quality of our education and research programs - including significant industry, government and community collaboration - offers you vast scope and opportunity for a long, fulfilling career.

It also enables us to attract high-calibre people in all facets of our operations, ensuring you will be surrounded by talented colleagues, many world-leading. Our work’s cutting-edge nature - not just in your own area, but across virtually the full spectrum of human endeavour - provides a constant source of inspiration.

Our culture is one that welcomes all and embraces diversity consistent with our Staff Values and Behaviour Framework and our values of integrity, respect, collegiality, excellence and discovery. We firmly believe that our people are our most valuable asset, so we work to grow and diversify the skills, knowledge and capability of all our staff.

We embrace flexibility as a key principle to allow our people to manage the changing demands of work, personal and family life. Flexible working arrangements are on offer for all roles at the University.

In addition, we offer a wide range of attractive staff benefits. These include: salary packaging; flexible work arrangements; high-quality professional development programs and activities; and an on-campus health clinic, gym and other fitness facilities.

Learn more at:

Your faculty’s broader role

The Faculty of Sciences, Engineering and Technology is a thriving centre of learning, teaching and research in a vast range of engineering disciplines, computer science - including machine learning, high-level mathematics and architecture, planning and landscape architecture. Many of its academic staff are world leaders in their fields and graduates are highly regarded by employers.

Learn more at:

If you have the talent, we’ll give you the opportunity. Together, let’s make history.

Click on the ‘Apply Now’ button to be taken through to the online application form. Please ensure you submit a cover letter, a full CV (including a publication list and statement of research expertise and interests) and upload a document that includes your responses to all of the selection criteria for the position as contained in the position description or selection criteria document.

Applications close 11:55 pm, 5 March, 2023.

For further information

For a confidential discussion regarding this position, contact:

Dr Angela Noack
Program Manager, Centre for Augmented Reasoning
P: +61 (08) 8313 8069

You’ll find a full position description below: (If no links appear, try viewing on another web browser or device)

The University of Adelaide is an Equal Employment Opportunity employer. Women and Aboriginal and Torres Strait Islander people who meet the requirements of this position are strongly encouraged to apply.