Postdoctoral Research Associate

The faculty seeks to appoint a Postdoctoral Research Associate to work in the Peninsula Collaboration for Health, Operational Research and Data Science (PenCHORD). This full time research post is split 0.5FTE on the UKRI Medical Research Council funded project STARS: Sharing Tools and Artefacts for Reproducible Simulations in healthcare; and 0.5FTE on the Health Service Modelling Associates (HSMA) programme.

This is a fixed term position until March 2026.

About STARS and HSMA and the work you will be involved with.

STARS is an Open Science project that aims to increase the quantity and quality of computer simulation models that are open for reuse by health researchers and the NHS. The post holder will conduct cutting edge research that builds on our preliminary research with Open Weight Local Large Language Models (e.g. Llama3, and Phi4) and Commerical models (e.g. Claude 3.7 and Gemini 2.5) to develop methods for generating simulation models of healthcare pathways in Python.

The Health Service Modelling Associates (HSMA) Programme is an online national training scheme for public sector analysts, clinicians and managers in data science and operational research techniques, as well as supporting them to apply these techniques in their organisations.

Students of HSMA work on an applied data science project (e.g. A&E modelling, or reducing delayed discharges from hospital). The post holder will primarily focus on research outputs from HSMA: identifying high impact projects, supporting the NHS with data science, and producing high quality academic articles for publication. The post holder will have opportunities to contribute to HSMA teaching, mentoring and content development.

About you

We are looking for an Associate Research Fellow to join STARS and HSMA until 31^st March 2026 in the first instance. We need you to have a high aptitude and passion for learning how to use new technology, and working productively with others who may have different skillsets and knowledge. You will need to be comfortable using Free and Open Source Software (FOSS) and have demonstrable experience in Python, and/or R or equivalent skills in another relevant language. We are not expecting you to be an expert in all forms of computer simulation, Large Language Models, or machine learning etc, but a working knowledge of data science research processes from a relevant quantitative discipline, and strong coding skills are essential. Experience of prompt engineering for Large Language Models productivity improvements is desirable. All research will be made open as it is produced; hence you will need skills in basic FOSS infrastructure and workflow tools (Git, Github, Quarto/Rmarkdown/JupyterBook). Experience of producing academic journal articles is essential.

You will likely have at least a Masters degree in Health Data Science, Data Science, Computer Science, Maths/Engineering, or a Medical Sciences subject, and either have a Ph.D. or the equivalent experience. Mostly, apart from some prior experience in FOSS, Data Science or modelling, we are looking for people who are willing to be flexible and who can conduct research, learn, and apply, new FOSS tools as needed. The PenCHORD team can provide training and support in the use of advanced simulation methods, Linux, FOSS infrastructure tools, and writing journal articles as needed.

Please ensure you read the Job Description.

Further information

For further information please contact Thomas Monks, e-mail t.m.w.monks@exeter.ac.uk or Dr Daniel Chalk, email: d.chalk@exeter.ac.uk.

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