Research Associate or Research Fellow in Computational Health Policy Modelling
Overview
The Centre for Health Economics and Policy Innovation at Imperial Business School is seeking a Research Associate or Research Fellow in Computational Health Policy Modelling. The successful candidate will play a central role in developing Health-GPS, a microsimulation model for non-communicable disease policy analysis. The appointment will be made at either the Research Associate or Research Fellow level depending on experience. This position is full-time and fixed-term for 24 months, with potential for extension depending on funding, and operates on a hybrid work arrangement based in the United Kingdom.
What you get
The salary for this position ranges from £50,733 to £67,351 per annum. The role involves contributing to major international projects including GOLDFINCH, JA Prevent NCD, and JACARDI, focusing on evaluating and designing effective prevention policies for chronic diseases.
Requirements
Applicants must hold a PhD, equivalent qualification, or be near completion in health economics, epidemiology, computer science, or a related field. Candidates need experience building or using microsimulation models or other quantitative policy tools, strong programming skills in at least one language such as Python, R, or C++, experience contributing to a shared codebase using version control like git, and experience working with large or longitudinal datasets. C++ experience and familiarity with applying AI or machine learning methods to health or policy modelling are highly desirable. Candidates applying for appointment as a Research Fellow must also demonstrate a strong publication record, experience contributing to funding proposals, and the ability to design and lead original research.
How to apply
Interested candidates should apply online with a cover letter explaining their motivation and relevant experience while indicating the level for which they are applying, a curriculum vitae, and contact details for two referees. For any queries, contact Prof. Franco Sassi.
Key dates
The closing date for applications is 2026-11-22.