This fully funded PhD opportunity at University College London (UCL), in partnership with Roche, focuses on the conceptualisation and validation of digital biomarkers to advance cardiovascular, renal, and metabolic (CVRM) drug development. CVRM diseases represent a major global health challenge, and this project aims to leverage digital health technologies and wearable sensors to enable continuous, non-intrusive patient monitoring and advanced data analytics. The research will facilitate early disease detection, support personalized treatment, and enhance clinical research in CVRM.

The project is situated at the intersection of clinical medicine, behavioural science, and data science. The successful candidate will rigorously conceptualise, validate, and apply digital biomarkers—such as physical activity, sleep patterns, and heart rate variability—to provide objective measures of treatment response and patient adherence. The work will be conducted at UCL's Department of Mechanical Engineering, with close integration into Roche's clinical development programs, particularly focusing on obesity and the rapid advancement of biopharmaceutical agents like GLP-1 therapies through clinical trials.

Core research questions include identifying meaningful aspects of health in CVRM patients, developing promising digital biomarkers from wearable technologies, and designing approaches to validate their accuracy, reliability, and clinical utility. The project will involve exploratory data science methods, observational studies, and the development of new data analysis approaches for candidate biomarkers. There may be opportunities to apply these digital biomarkers to clinical trial data and real-world settings.

The studentship is funded by the EPSRC Centre for Doctoral Training in Digital Health Technologies and Roche, covering tuition fees at the home rate and an annual stipend. The program offers cohort learning, annual doctoral conferences, partner sandpits, clinical shadowing, training workshops on ethics and entrepreneurship, and a 3-month industry secondment. Students will benefit from mentorship and resources from both UCL and Roche, gaining exposure to cutting-edge academic and industry research.

Applicants should have a Master's degree in a relevant quantitative field (e.g., Computer Science, Data Science, Statistics, Biomedical Engineering, Health Informatics), strong programming skills (Python/R), experience with machine learning and time-series/sensor data analysis, and an interest in clinical research and drug development. Excellent communication skills and the ability to work collaboratively in interdisciplinary teams are essential. International candidates are encouraged to apply.

To apply, submit a CV, cover letter, academic transcripts, and contact details for two academic referees to CDT Manager Jamie Kozak ([email protected]). For informal inquiries, contact Prof. Dr. D. Hill ([email protected]) or Dr. Adrian Derungs ([email protected]). The application deadline is December 15, 2025, with interviews in January and the project starting in February.