A PhD opportunity in biostatistics is available at the University of Melbourne, in collaboration with the Clinical Epidemiology and Biostatistics Unit (CEBU) at the Murdoch Children’s Research Institute (MCRI). The research will focus on developing and applying statistical methods to address challenges in adaptive platform trials (APTs), which are innovative clinical trial designs used in medical research. This position is ideal for candidates interested in statistical methodology, clinical epidemiology, and the application of statistics to medical and health research.

The successful applicant will join a vibrant research environment at MCRI and the University of Melbourne, working under the supervision of Professor Katherine Lee, Dr Chris Selman, and Dr Melissa Middleton. The project will provide opportunities to contribute to methodological advances in biostatistics and to collaborate with leading researchers in clinical trials and epidemiology.

Applicants should demonstrate a strong interest in statistical methodology and biostatistics. Required application materials include an outline of your interest in statistical methodology, a CV, and academic transcripts. While no explicit degree or GPA requirements are mentioned, a background in statistics, mathematics, or a related field is expected. Candidates are encouraged to contact the supervisors to discuss their interest prior to applying.

The successful candidate will be supported to apply for a PhD scholarship at the University of Melbourne. The results of the scholarship application will be available by 27 March 2026, and the PhD program is expected to begin in April 2026 or later, depending on the candidate’s circumstances. No specific details on funding amount or tuition coverage are provided at this stage.

To apply, send an expression of interest by email to Professor Katherine Lee, Dr Chris Selman, and Dr Melissa Middleton by 12th January 2026. The expression of interest should include an outline of your interest in statistical methodology, your CV, and academic transcripts. Early discussions with the supervisors are encouraged.

For more information, refer to the LinkedIn post or contact the supervisors directly via the provided email addresses.