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Flinders University 2025 Cancer Epidemiology, Machine Learning & Data Sharing

Help shape the future of cancer care through better data. This PhD scholarship offers the opportunity to work with a leading research team using clinical trials and real-world data to build machine-learning models, improve the prediction of treatment outcomes, and promote responsible data sharing.
The successful applicant will join a supportive and collaborative team based at Flinders University, working closely with data scientists, oncologists, and international collaborators. The research will inform real-world decisions in oncology and contribute to tools that improve patient care.
Eligibility Criteria for Flinders University 2025 Cancer Epidemiology, Machine Learning & Data Sharing
They welcome applicants who:
- Australian citizens
- Hold an Honours or Master’s degree in epidemiology, biostatistics, computer science, public health, pharmacy, or a related field
- Are passionate about improving the health outcomes of patients with cancer
- Possess excellent written and verbal communication skills
- Can work collaboratively in a multidisciplinary team
Benefits of Flinders University 2025 Cancer Epidemiology, Machine Learning & Data Sharing
- Tax-free stipend of $33,990 to $50,000 AUD per annum, depending on experience and eligibility
- Up to 3.5 years of full-time support
- Tuition fee waiver support available for eligible candidates
- The team is well-funded to support research training, conference travel, and necessary computing resources
How to Apply
Please submit the following by 31 May 2025 to: ashley.hopkins@flinders.edu.au
- Cover letter (1 page) outlining your interest in the project, suitability, and career goals
- Curriculum Vitae (max 5 pages), including academic qualifications, GPA, publications (if any), and referees
- Academic transcript (PDF format)
Subject line: PhD Application – Cancer Data & Machine Learning
Filename format: e.g., CV_YourName, CoverLetter_YourName, Transcript_YourName
For more details, visit Flinders University scholarrship webpage
Application Link(s)
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