Project opportunity
This Earmarked Scholarship project is aligned with a recently awarded Category 1 research grant. It offers you the opportunity to work with leading researchers and contribute to large projects of national significance.
Knee osteoarthritis (OA) affects >100 million people globally, causing pain, dysfunction, and psychological stress, thereby diminishing quality of life and imposing an enormous socioeconomic burden. Predicting knee OA onset and progression on an individual basis will focus the clinical resources required to those who need it and potentially help improve clinical outcomes. In this project, the candidate will develop novel artificial intelligence (AI) / Deep Learning (DL) methods for extracting and handling sparse/lower quality imaging and modelling data commonly originate from clinical environments such as hospitals in order to make accurate predictions of knee OA onset and progression. The candidate will have the opportunity to work with the leaders of automated OA analysis and modelling in Australia, as well as be part of a large team of AI/DL researchers at UQ.
Scholarship value
As a scholarship recipient, you'll receive:
- living stipend of $32,192 per annum tax free (2023 rate), indexed annually
- tuition fees covered
- single Overseas Student Health Cover (OSHC)
Supervisor
School of Information Technology and Electrical Engineering
Email: shekhar.chandra@uq.edu.au
Preferred educational background
Your application will be assessed on a competitive basis.
We take into account your
- previous academic record
- publication record
- honours and awards
- employment history.
A working knowledge of image processing, information retrieval, computer vision, medical imaging and/or bio-mechanical modelling would be of benefit to someone working on this project.
The applicant will demonstrate academic achievement in the field(s) of electrical/mechanical engineering, robotics, mechatronics engineering, data science, biomedical engineering, computer vision, computer science or mathematics and the potential for scholastic success.
A background or knowledge of deep learning is highly desirable.
Latest commencement date
If you are the successful candidate, you must commence by Research Quarter 2, 2023. You should apply at least 3 months prior to the research quarter commencement date.
If you are an international applicant, you may need to apply much earlier for visa requirements.
How to apply
You apply for this project as part of your PhD program application.