James Carpenter

This PhD project at the University of Cambridge's MRC Biostatistics Unit focuses on developing advanced statistical approaches for sample size determination in clinical trials that utilize novel digital endpoints. With the increasing integration of wearable and implantable devices in clinical research, digital outcome measures are becoming more prevalent, offering the potential for more sensitive and relevant assessments of patient health. However, these measures often present complex statistical challenges, such as zero-inflation, skewness, autocorrelation, and intricate missing data patterns, making traditional sample size calculation methods inadequate. The project aims to create robust, simulation-based strategies for determining sample sizes in phase II and III clinical trials using digital endpoints. It will leverage real-world accelerometer data from the Mobilise-D validation study and the ongoing EJS ACT-PD trial for Parkinson’s disease. The research will encompass a variety of trial designs, including parallel-group, longitudinal, and cross-over studies, and will explore both parametric and non-parametric analysis methods. Additionally, the project will develop methods for sample size re-estimation and produce software tools and guidance documents to support trialists in implementing digital outcomes as primary endpoints. The supervisory team includes Dr Mia Tackney (NIHR Advanced Fellow at MRC-BSU), Professor James Carpenter (Professor of Medical Statistics at LSHTM and MRC Investigator at UCL), and Sofía Villar (Programme Leader and MRC Investigator at MRC-BSU). The student may also benefit from an industry placement with a pharmaceutical company or clinical research organization, gaining practical experience in trial operations and digital data analysis. Opportunities for patient and public involvement and engagement (PPIE) training and activities are available through the CUH biomedical PPIE group and other collaborators. Applicants should have a strong quantitative background, ideally in statistics or mathematics, with experience in statistical programming and data analysis. Interest in clinical trials, digital health, and simulation methods is highly desirable. The studentship provides funding (details to be confirmed) and is open to candidates meeting the University of Cambridge's academic and English language requirements. The application deadline is 26 January 2026, and prospective applicants are encouraged to contact Dr Mia Tackney ([email protected]) before 2 January 2026 to discuss their interest. For full application details, visit the MRC DTP website .