Imperial College London

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Research Associate or Research Fellow in Computational Health Policy Modelling @ Imperial College London

London, England, GBHybridTemporary
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About this role

Build the Next Generation of Health Policy Simulation Models

Do you want your research to influence how governments design policies to prevent chronic disease? Are you excited by the challenge of combining data, simulation, and policy to tackle the world’s biggest health problems?

The Centre for Health Economics & Policy Innovation (CHEPI) at Imperial Business School is seeking a Research Associate / Research Fellow in Computational Health Policy Modelling to play a central role in developing Health-GPS — our state-of-the-art microsimulation model for non-communicable disease (NCD) policy analysis. Appointment will be made at Research Associate or Research Fellow level, depending on experience.

Why This Role Matters

Chronic diseases such as diabetes and cardiovascular disease remain leading causes of illness and premature death worldwide. Yet, the tools available to evaluate and design effective prevention policies are still evolving. Health-GPS provides a framework to explore how changes in diet, physical activity, and related risk factors affect long-term population health and economic outcomes.

Health-GPS represents the gradual accumulation and interaction of individual-level risk factors — such as BMI, diet, and income — offering insights into the potential impact of different policy interventions over time.

You will help develop and apply this model across major international projects including:

  • GOLDFINCH – estimating the effects of fiscal policies on ultra-processed food consumption.
  • JA Prevent NCD – a European Joint Action on integrated strategies for NCD prevention.
  • JACARDI – a European initiative to reduce cardiovascular and diabetes risk.

What You’ll Do

  • Contribute to the architecture, development, optimisation, and maintenance of Health-GPS, writing and reviewing code in its C++ codebase and ensuring its continued scientific and policy relevance.
  • Work with colleagues to plan and deliver modelling work across multiple projects, producing high-quality outputs on time.
  • Help integrate new methodologies, including AI and machine-learning approaches, into simulation design.
  • Conduct quantitative analyses to estimate the health and economic impact of proposed policies.
  • Identify and manage relevant datasets in collaboration with internal and external partners.
  • Communicate findings through academic papers, policy briefs, and stakeholder workshops.
  • Contribute to funding proposals and the expansion of CHEPI’s modelling activities.

What We’re Looking For

We’re seeking a creative and technically strong individual with:

  • A PhD (or equivalent, or near completion) in health economics, epidemiology, computer science, or a related field.
  • Experience building or using microsimulation models or other quantitative policy tools.
  • Strong programming skills in at least one language (e.g. Python, R, or C++), and experience contributing to a shared codebase using version control (e.g. git).
  • Experience working with large or longitudinal datasets.
  • The ability to translate complex model outputs into actionable policy insights.

Experience with C++ is highly desirable. Experience applying AI or ML methods to health or policy modelling is also desirable.

Candidates for appointment as Research Fellow should also demonstrate a strong publication record, experience contributing to funding proposals, and the ability to design and lead original research.

How to Apply

Interested? Please read the job description and person specification, then apply online with:

  • A cover letter explaining your motivation and relevant experience, and indicating the level (Research Associate or Research Fellow) for which you are applying.
  • Your CV.
  • Contact details for two referees.

This position is full-time and fixed-term for 24 months, with potential for extension depending on funding.

For queries, contact Prof. Franco Sassi ([email protected])

Skills

Higher EducationAcademic or ResearchEconomicsComputer ScienceMedicine & DentistryHealth & MedicalComputer SciencesAcademic

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