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Location: White City (hybrid)
About the role:
The post is within the SHIELD Joint Action (Strategies for Health Interventions to Eliminate Infection-related Cancers). The overall aim of SHIELD is to reduce premature morbidity and mortality caused by infections that lead to cancer, including human papillomavirus (HPV), hepatitis B and C viruses (HBV, HCV), human immunodeficiency virus (HIV), and tuberculosis (TB), through the development and implementation of coordinated, evidence-based prevention strategies across European countries.
This post will contribute specifically to the multi-disease modelling framework, which aims to generate integrated, policy-relevant evidence to inform the optimal design and prioritisation of prevention programmes.
The post is funded under the EU4Health programme, and the post-holder will work within a multidisciplinary and international consortium of academic institutions, public health agencies, and policy stakeholders. The modelling work will play a central role in supporting SHIELD’s objective to identify effective combinations of interventions, address barriers to implementation (including stigma and health system limitations), and translate analytical outputs into actionable recommendations for cancer prevention policy and practice.
What you would be doing:
The post-holder will lead the development and delivery of the multi-disease modelling work within SHIELD, contributing as a key member of a large, multidisciplinary and international consortium, providing technical guidance and mentoring to junior researchers where appropriate.
The primary objective is to design, implement, and operationalise a flexible, integrated modelling framework that allows disease-specific models (e.g. HPV, HBV, HCV) to be incorporated within a common structure. This framework will enable coordinated, cross-disease analyses to support more holistic evaluation of cancer prevention and treatment strategies across EU Member States. The post-holder will work closely with partner modelling groups, supporting integration of their models and generating high-quality, policy-relevant evidence.
What we are looking for:
- Hold a PhD in epidemiology, mathematical modelling, statistics, computer science, or a closely related discipline, or equivalent research, industrial or commercial experience.
- *Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant.
- Experience in infectious disease modelling, health systems modelling, or related quantitative research.
- Strong programming experience, preferably in Python, with evidence of developing and maintaining analytical or simulation code.
- Experience working with complex datasets, including data cleaning, harmonisation, and analysis.
What we can offer you:
- The opportunity to continue your career at a world-leading institution and be part of our mission to continue science for humanity.
- Grow your career: gain access to Imperial’s sector-leading dedicated career support for researchers as well as opportunities for promotion and progression.
- As a member of research staff you have 10 development days to use to develop your skills and explore your career prospects
- Sector-leading salary and remuneration package (including 41 days off a year and generous pension schemes).
- Be part of a diverse, inclusive and collaborative work culture with various staff networks and resources to support your personal and professional wellbeing.
Further Information
Please note that this is a PhD level role but candidates who have not yet been officially awarded will be appointed as a Research Assistant.
This role is for a full-time and fixed-term contract until 31st October 2028 (part-time arrangements can be discussed at the interview).
If you require any further details about the role, please contact:
Dr Tara Mangal at t.mangal@imperial.ac.uk.