ARC Research Associate - Australian Institute for Machine Learning

The University of Adelaide is one of Australia's leading Group of Eight, research-intensive universities and is consistently ranked among the top 1% of universities in the world. Established in 1874, it is Australia's third oldest university with a strong reputation for preparing educated leaders and delivering research outcomes that contribute to local, national and global wellbeing.

University of Adelaide employees enjoy a range of benefits and favourable work conditions that include opportunities for career development and advancement. 

The Faculty of Engineering, Computer and Mathematical Sciences is one of five faculties at the University of Adelaide. It is a centre for learning, teaching and research in a vast range of engineering disciplines, computer science and high level mathematics. Academic staff are world leaders in their fields of consulting, advanced fundamental and applied research. Graduates are highly regarded by employers. The faculty offers an intellectually exciting and innovative environment in which to work. 

We seek to fill 1 post-doctoral position within the Australian Institute for Machine Learning. The Institute conducts state-of-the-art research in medical image analysis, computer vision, and machine learning. The School of Computer Science at the University of Adelaide hosts the largest computer vision and image analysis research group in Australia, with over 60 members including academics, research staff and students.  We work on a mixture of fundamental and commercially oriented research projects in medical image analysis, computer vision, and machine learning.  We have a very consistent track record of publications in the top conferences and journals (MICCAI, NIPS, ICCV, CVPR, ECCV, ISBI, TMI, MedIA, TPAMI, TIP).

The post will be funded from an Australian Research Council Discovery Project Grant awarded in 2018 to Associate Prof. Gustavo Carneiro and colleagues. The project will develop novel methods for discovering and visualising optimal biomarkers from chest computed tomography images based on extensions of recently developed deep reinforcement learning methods. Likely research areas will include: reinforcement learning, meta-learning, learning with noisy labels, integration of clinical variables with imaging data, benchmarking and evaluation of deep learning using large clinical datasets, Bayesian deep learning, and large-scale object detection, segmentation and recognition.

The ideal applicant will have a PhD in Computer Science, Mathematics, Engineering or other related discipline, and have a strong publication record, commensurate with opportunity and experience. The applicant will have existing expertise in medical image analysis, computer vision, machine learning, and/or statistical and numerical methods.

Salary:

Level A Step 6 ($85,307 per annum)

Superannuation:

An employer contribution of 9.5% applies

Term of position:

This fixed-term contract is available immediately for 1 year, renewable for a second year depending on performance.

Position requirements

To be successful you should have:

1. Have or be about to complete a PhD in Medical Image Analysis, Computer Vision, Machine Learning, Artificial Intelligence or other closely related area
2. A good first degree in Engineering, Computer Science or a related discipline
3. Publication record commensurate with experience and opportunity
4. A strong work ethic, and the ability to work well independently, and as a member of a broader team, including with industrial partners
5. Expertise and experience in computer programming, especially in Python (tensorflow and pytorch), C++ and Matlab
6. Fluency in written and spoken English, with an ability to communicate scientific ideas to an expert audience, both orally and written

Please address and upload your responses to the selection criteria within the online application. If you have any technical queries regarding this position, please contact A/Prof Carneiro, gustavo.carneiro@adelaide.edu.au

If you have any administrative queries regarding this position, please contact Ms Thuy Mai, thuy.mai@adelaide.edu.au

Please note if the selection criteria link is not appearing, you will need to view on another device.

Closing Date: May 15th

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

Download the Position Description