PhD Scholarship "Cancer Biology and Machine Learning"

Details - La Trobe University PhD Scholarship "Cancer Biology and Machine Learning"La Trobe University PhD Scholarship "Cancer Biology and Machine Learning"

Apply now Job no: 569338
Work type: Fixed Term
Location: Melbourne (Bundoora)
Categories: Computing Engineering & Mathematical Sciences

• Position to be based at La Trobe Melbourne Campus.
• An amount of $40,000 per annum for 3.5 years, fee relief additional, fortnightly stipend.

The position:

This prestigious La Trobe University scholarship, in partnership with the Australian Office of National Intelligence, 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. The resulting multipurpose machine learning workflows will lead to rapid precision diagnoses and effective individualized cancer care plans. Coding and user interface development skills will be developed.

This scholarship is open only to Australian citizens, Australian permanent residents, or New Zealand special category visa holders. The Expression of Interest will remain open until the positions are filled.

Benefits of the scholarship include:

• a stipend scholarship for three and a half years, with a value of $40,000 per annum (pro-rata), to support your living costs.
• a fee-relief scholarship for up to four years.
• opportunities to work with La Trobe's outstanding researchers in state-of-the-art laboratories and have access to our suite of professional development programs.
• a collaborative project, including time spent with the Olivia Newton-John Cancer Research Institute and CSIRO.
• opportunities to travel to conferences in Australia and overseas.

Eligibility criteria:

To be eligible to apply for this scholarship, applicants must:

• be Australian citizens, Australian permanent residents, or New Zealand special category visa holders (strict requirement).
• should they be selected, agree to be enrolled full-time and undertaking their research at the La Trobe University Melbourne (Bundoora) campus.

In selecting successful applicants, we prioritise applications from candidates who:

• have an outstanding record of prior performance.
• have completed a Masters by Research or other significant body of research, such as an honours research thesis or lead authorship of a peer-reviewed publication, assessed at a La Trobe Masters by research standard of 75 or above.
• have outstanding grounding in one or more relevant disciplines including cancer biology, cancer medicine, physics, chemistry, , engineering, machine learning / data science, coding.

How to apply:

This is an Expression of Interest process. To express your interest in applying, candidates must supply the following information via email tooni.scholarship@latrobe.edu.au :

• a statement outlining:
  - their motivation and suitability for this opportunity;
  - their specific skills and experience and how these are relevant to the PhD project;
  - how this opportunity fits with their career plans.
• a statement confirming that you are currently an Australian citizen, Australian permanent resident, or New Zealand special category visa holder.

Shortlisted applicants will be required to attend an interview and may be asked to participate in further evaluation activities.

The successful applicant will be required to have a working with children check (WWCC) prior to commencing the position, to be paid for by the applicant.

The University will carefully review and consider your expression of interest for this scholarship. Successful candidates will be invited to submit a full application for candidature and scholarship.

See also:

https://www.latrobe.edu.au/study/scholarships/other/connecting-spatial-and-spectral-information-understanding-complex-materials-systems-at-the-molecular-level-with-machine-learning-phd-scholarship

Closing date for applications: 31/10/2025

Advertised: 29 Jul 2025 AUS Eastern Standard Time
Applications close:

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