Grant-funded Researcher

1 week ago

Adelaide Region SA, Australia The University of Adelaide Full time

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

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 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.


This postdoctoral role will investigate:

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.

Training efficiency:

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

Specializing:

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

To be successful you will need:

  • A PhD in computer science or related discipline, or equivalent industry experience
  • Programming experience and expertise in Python, or C++, or other relevant languages
  • Experience and demonstrable expert knowledge in one or more of the following areas: multi-modal, multi-task, robust and intelligent perception
  • 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:

  • Has the experience and/or ability to contribute to the promotion of research capabilities to industry and the wider community
  • 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 ac

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