Post Doctoral Research Fellow

Description:

Full Job Description

The position is funded under an Australian National Health and Medical research Council Grant: “Automated methods for evaluating structural vascular disease” and Department of Health WA Near-miss grant, “A novel machine-learning approach to reduce falls in older community-dwelling Australians”. The successful applicant will contribute to novel theory and methods in applying Deep Learning methods to problems in Medical and Health related image analysis. Particularly, the key focus will be to develop and assess methods to extract calcification measures off images of the abdominal aorta and correlate these measures with clinical data as well as to develop methods to predict falls in the elderly using whole body DXA scans.

The Role

The School is looking for enthusiastic Post-doctoral Research Fellow who possesses knowledge and expertise in areas including:

Machine Learning

Deep Learning

Computer Vision

Medical Image Processing

What you will do

The successful candidate/s are expected to promote and publish in these areas of research and engage in the supervision and training of research students and project team members.

Skills & Experience

You must have a PhD in an appropriate field (e.g., Computer Science, Mathematics, Electrical Engineering) and expertise in one or more of the areas listed above will be preferred. Strong mathematical ability will be an advantage. Publications in top computer vision venues such as CVPR/ICCV/ECCV/MICCAI/TPAMI or top machine learning venues such as NIPS will also be highly regarded.

The successful applicant will also demonstrate personal attributes that are congruent with the University’s values of Integrity, Respect, Rational Inquiry and Personal Excellence.