Background

Reconstructing routes and drivers of transmission by comparing pathogen genomes is an area of intense research within the wider domain of ‘phylodynamics’, but statistical methods currently lack the sophistication to handle common complexities in real data, notably horizontal gene transfer and idiosyncratic sampling.

RESEARCH EXPERIENCE, RESEARCH METHODS AND TRAINING

The aim of this project is to develop better population genetics models of pathogen evolution and epidemiology, and apply them to in-house data comprising 1000s of genomes to improve our understanding of transmission processes. This data science project combines statistical genetics, computational biology and comparative genome analysis, building on previously developed tools (e.g. PMID:25675341, PMID:26267488, PMID:33444378). Training will be given on-the-job by members of the research group and our collaborators. University courses are available in R, python and scientific computing.

FIELD WORK, SECONDMENTS, INDUSTRY PLACEMENTS AND TRAINING 

The supervisors are members of the international Modernising Medical Microbiology consortium. Group members will join weekly lab meetings and attend conferences.

PROSPECTIVE STUDENT

This project would suit biologists with prior experience of quantitative methods and programming or physical and mathematical scientists with knowledge of genetics and evolution.

Supervisors