Research Associate

• Hold a PhD in infectious disease epidemiology, computational biology, population biology, biostatistics or a related quantitative discipline, or equivalent research, industrial or commercial experience *Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant.
• Demonstrated experience developing mathematical and/or statistical approaches to answer complex biological questions.
• Experience conducting quantitative analyses of complex biological data using rigorous analytical approaches.
• Experience disseminating research through high-quality scientific outputs, such as peer-reviewed publications, preprints, software tools and conference presentations.
• Advanced programming skills in R and/or Python.
• Knowledge of, or strong interest in learning about, infectious disease epidemiology.

• 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 43 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.

We invite applications for a Research Associate to develop novel methods for pathogen genomic epidemiology in the Department of Infectious Disease Epidemiology, School of Public Health, Faculty of Medicine, Imperial College London.

The post is funded by a Wellcome Early-Career Award and will be based in a new group within the Department of Infectious Disease Epidemiology. The group develops scalable mathematical and statistical approaches leveraging large pathogen genome datasets to understand the determinants of infectious disease transmission. Our work combines data analysis, genomic epidemiology, mathematical modelling and statistical inference to answer public health relevant questions. We are committed to building a positive and inclusive environment, where all team members feel that they belong and are excited to do research. We recognise the systemic barriers that exist in higher education and research, particularly for people from historically marginalised groups. Applicants from groups underrepresented in science and research are particularly encouraged to apply.

The successful candidate will develop and apply statistical and computational methods to characterise infectious disease transmission from pathogen genomic data, with an initial focus on seasonal influenza and opportunities to extend the work to other pathogens. Projects will build on approaches developed in the group that rely on genetically proximal sequences and do not require full phylogenetic tree reconstruction. The work will include a combination of method development and validation, computational simulations and data analysis, which can be balanced depending on the postholder's interests and experience. This work is fundamentally interdisciplinary, combining infectious disease epidemiology, pathogen evolution, genomic epidemiology, mathematical modelling, statistical inference and quantitative data analysis.

We do not expect candidates to be experts in all these areas, and welcome applicants with a strong foundation in one or more relevant disciplines who are enthusiastic about developing expertise across these areas.

This is a full-time and fixed-term contract for two years. The expected start date for this post is 01st February 2027 (with flexibility on the start date), and the contract end date will be 31st January 2029.