Biostatistics PhD

Overview

The Department of Biostatistics is one of the largest departments of Biostatistics in the UK, undertaking high-impact research in statistical genetics, pharmacogenetics, joint modelling of longitudinal and time-to-event data, multivariate data analysis, stereology, multi-source evidence synthesis and clinical trials. We have a sustained track record of research funded by the MRC, Wellcome Trust, Horizon 2020 and NIHR, and is committed to excellence in methodological and applied research. This provides an ideal environment for esteemed students to develop new methodological skills and applications to important health challenges in stratified medicine, infections, regenerative medicine and public health.

Staff and students are undertaking research involving groundbreaking basic science and life-changing therapies.

We have expertise in methodological research and a track record of national and international collaboration in high quality research across a broad range of applied health research interests:

Evidence synthesis
Clinical trials
Development of core outcome sets
Recruitment and retention of participants
Meta-analysis
Health informatics
Pharmacogenetics and statistical genetics
Applied health research.

The department provides an umbrella for cross-disciplinary units and initiatives, including the Clinical Trials Research Centre and the Medical Research Council North West Hub for Trials Methodology Research.

We are currently involved in the supervision of several students whose projects cover a wide range of topics, both in biostatistics and related health research fields. The development of, and support for, researchers is a high priority in the department.

Our research interests include:

Clinical trials
Survival data analysis
Multivariate and multilevel data analysis
Methods for evaluating biomarkers
Statistical pharmacogenetic
Joint modelling of longitudinal and time-to-event data
Pharmacokinetics
Pharmacodynamics personalised dosing algorithms
Statistical performance monitoring
Quality of life data analysis.