- Fixed-term or Casual Contract, up to 6 months, Joondalup Campus
- Open to candidates with relevant work rights
SCHOOL OF SCIENCE, COMPUTING AND SECURITY
JOONDALUP CAMPUS
HEW5 - FIXED-TERM OR CASUAL CONTRACT
FULL-TIME OR PART-TIME
CONTRACT FOR UP TO 6 MONTHS
Overview
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”. Successful candidate/s will contribute to the application of existing Deep Learning methods to problems in Medical and Health related image analysis. Particularly, the key focus will be to apply machine learning 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 Research Assistants who possess knowledge and expertise in applications in the following areas:
- Machine Learning
- Deep Learning
- Computer Vision
- Medical Image Processing
What you will do
The successful candidate/s are expected to run deep learning networks already developed by our group to test unlabelled 2D images. The candidate/s will be trained on the specifics of these networks.
Skills & Experience
You should possess the skills of independently running deep learning models in Pytorch. You must have an undergraduate degree in an appropriate field (e.g., Computer Science, Mathematics, Electrical Engineering). Strong mathematical ability will be an advantage.
The successful applicant will also demonstrate personal attributes that are congruent with the University’s values of Integrity, Respect, Rational Inquiry and Personal Excellence.
Benefits & Remuneration
For fixed-term candidates, this position attracts remuneration of a Hew 5 $75,821 - $84,254 p.a plus 17% University superannuation contribution. For casual candidates, this position attracts remuneration of $48 per/hour plus 10.5% University superannuation contribution.
ECU supports a work/life balance for staff. Benefits such as flexible working arrangements may also be negotiated to meet your personal circumstances.
For information on the benefits of working at ECU, please visit our Employment Opportunities website.
Contact
Interested applicants are encouraged to email Dr Zulqarnain Gilani [email protected]
How to Apply
Application is through the University recruitment website and you should include pdf copies of a full CV, relevant documents such as transcripts of undergraduate results, and a covering letter briefly summarising your suitability for the role and including the names and contact details of at least two relevant referees.
Closing Date
Applications close on Monday 27 March, 2023 at 11.30pm (AWST).
Open to applicants who have working rights in Australia.
ECU is a diverse and inclusive workplace reflecting the differences in society. Specific strategies and initiatives are in place to address underrepresentation of specific groups. Applications are encouraged from suitably qualified people from all backgrounds. Aboriginal and Torres Strait Islander people are strongly encouraged to apply.
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