PhD in Biostatistics, University of Leicester

4-year PhD studentship at University of Leicester in collaboration with University of Birmingham and AstraZeneca, for candidates with strong statistical background.


Title: Model-driven and data-driven solutions for regulatory and HTA decision-making to address emerging challenges in drug development in cancer

Supervisors: Prof Sylwia Bujkiewicz (UoL), Prof Richard Riley (UoB) and Dr Sam Khan (UoL)

Industry partner: Dr Daniel Jackson, AstraZeneca

Collaborator: Dr Janharpreet Singh (UoL)

This project will tackle methodological challenges occurring at different milestones of drug development process, including regulatory approvals and particularly HTA decision-making by agencies such as NICE, when evaluating new cancer therapies. Modern cancer therapies are often targeted to small subsets of patients who harbour a particular biomarker. Survival data from clinical trials evaluating the effectiveness of therapies in a cancer subtype may be limited. You will explore use of other sources of data; based on alternative outcomes, study types or other cancers, which may need to be synthesised efficiently for reliable policy decisions. You will apply a range of modern tools from biostatistics (including Bayesian statistics, meta-analysis and survival analysis), epidemiology and data science and develop novel approaches for evaluation of cancer therapies.

This project is part of an exciting collaboration with University of Birmingham and AstraZeneca. You will benefit from an experienced supervisory team with expertise in statistics and oncology and an industry partner. This PhD in Biostatistics will provide you with an opportunity to develop advanced analytical skills, gain insight into drug development and decision-making processes and influence important decisions in healthcare. A suitable candidate will have MSc in Statistics, Medical Statistics or a related discipline.


See for more details.


Application deadline Friday 12 January 2024. Open to UK and international students.


Webinars for prospective applicants are being held on Monday 11 December at 18:30 GMT and Wednesday 13 December 2023 at 11:00 GMT.


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