Research Scientist
2 days ago
This prestigious scholarship will be awarded to an outstanding applicant interested in connecting spatial and spectral information to understand complex materials systems at the molecular level with machine learning.
The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models to individualise tumour type, associated biomarkers and genomic characteristics to high precision.
This project aims to lead to rapid precision diagnoses and effective individualized cancer care plans. Coding and user interface development skills will be developed.
- Required skills and qualifications include a strong grounding in one or more relevant disciplines including cancer biology, physics, chemistry, engineering, machine learning / data science, coding.
Benefits of this opportunity include:
- a stipend scholarship for three and a half years, to support your living costs.
- a fee-relief scholarship for up to four years.
- opportunities to work with leading researchers in state-of-the-art laboratories and have access to professional development programs.
- a collaborative project, including time spent with other research institutions.
- opportunities to travel to conferences in Australia and overseas.
To be eligible, applicants must be Australian citizens, Australian permanent residents, or New Zealand special category visa holders. They should also agree to be enrolled full-time and undertaking their research at a major university campus.
In selecting successful applicants, we prioritise applications from candidates who have an outstanding record of prior performance and have completed significant research projects.
We are looking for highly motivated individuals who can contribute to our team's goals. If you are passionate about cancer research and machine learning, please express your interest in applying for this opportunity.
Eligible candidates will be required to attend an interview and may be asked to participate in further evaluation activities.
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