Join a Wellcome-funded group in Imperial College London to advance methods for pathogen genomic epidemiology. You will develop statistical and computational techniques to infer transmission patterns from genome data, starting with seasonal influenza. This role blends method development with data analysis and simulations in a collaborative, interdisciplinary environment. You will contribute to high-impact public health research and have opportunities for career development and progression. This is an exciting chance to shape scalable approaches that impact infectious disease understanding.
Pay / Benefits
career development support
10 development days
sector-leading salary
43 days off per year
generous pension schemes
diverse and inclusive culture
Responsibilities
Develop and apply statistical/computational methods to characterize transmission from pathogen genomic data
Focus initially on seasonal influenza with potential extension to other pathogens
Engage in method development, validation, simulations and data analysis
Work in an interdisciplinary setting combining epidemiology, evolution, genomics, modelling and inference
Balance project work according to interests and expertise
Key requirements
PhD or equivalent in a quantitative field (or eligibility for Research Assistant role)
Demonstrated experience building mathematical or statistical approaches to solve complex biological questions
Experience performing quantitative analyses on complex biological data using rigorous methods
Evidence of disseminating research through publications, preprints, tools, or presentations
Advanced programming skills in R and/or Python
Knowledge of infectious disease epidemiology or strong interest to learn
Cross-disciplinary collaboration
Curiosity and willingness to develop expertise across fields
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