Research Fellow in Medical Statistics and Health Data Science

The role

We are seeking an ambitious and collaborative Research Fellow (50% FTE) to join a multidisciplinary team working at the forefront of causal inference in trusted research environments. This exciting role builds on nationally significant work evaluating COVID-19 vaccine effectiveness and will contribute to the development of the target trial emulation framework using large-scale electronic health record (EHR) data.

The successful candidate will play a central role in developing and applying advanced causal inference approaches, as well as line managing more junior colleagues in the electronic health records team and contributing to grant applications. The post also offers opportunities to explore scalable approaches for handling missing data efficiently in complex healthcare datasets.

Working closely with colleagues across Bristol and partner institutions throughout the UK, you will contribute to high-impact methodological and applied research with direct relevance to population health and healthcare policy.

Hybrid working is not available for this role. 

What will you be doing?

The post-holder will lead and contribute to methodological and applied research using causal inference approaches within large electronic health record datasets. Key responsibilities include developing and applying target trial emulation and investigating approaches to handling missing data. The role involves collaborating with academic and national partners, producing high-quality publications, presenting findings at conferences, and supporting open and reproducible research practices through transparent coding and documentation. The post-holder will also contribute to grant applications, support software development, supervise research students, and line manage more junior colleagues within the team.

You should apply if

You should apply if you have experience in quantitative health research, statistics, epidemiology, data science, or a related discipline, with expertise in analysing large and complex datasets. Candidates should have a strong understanding of causal inference methods and an interest in target trial emulation and missing data methodology. Experience using statistical programming languages such as R or Python, producing peer-reviewed publications, and working collaboratively within multidisciplinary research teams is essential. You should also be motivated to contribute to open and reproducible research, support junior colleagues, and engage with national and international research collaborations.

Additional information

Contract type: Open-ended with funding for 30/06/2029

Work pattern: Part-time/ 0.5FTE

Shift pattern: 17.5 hrs/week

This advert will close at 23:59 UK time on 21/06/2026

For informal queries please contact:

Jonathan Sterne (Professor of Medical Statistics and Epidemiology) - Jonathan.sterne@bristol.ac.uk

Our strategy and mission

We recently launched our strategy to 2030 tying together our mission, vision and values.

Available documents

• Faculty of Health and Life Sciences - October 2024.pdf
• ACAD108609 - RF in Medical Statistics and Health Data Science JD.pdf

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