PhD Studentship: Understanding drug resistance in M. tuberculosis by applying machine learning to a national genomic census

Overview

The School of Biosciences at the University of Birmingham offers a PhD studentship focused on understanding drug resistance in M. tuberculosis through the application of machine learning to a national genomic census. Tuberculosis remains a leading infectious cause of death worldwide, and elimination efforts face challenges due to drug resistance. While most resistance studies rely on biased datasets enriched for resistant isolates, this joint project between the University of Birmingham and the UK Health Security Agency utilizes a comprehensive national collection of M. tuberculosis genomes from England. This collection integrates both drug-susceptible and drug-resistant isolates alongside linked enhanced surveillance records and epidemiological data.

What you get

The selected student will acquire expertise in microbial genomics, bioinformatics, and applied machine learning. The research investigates how advanced machine learning methods can enhance surveillance for tuberculosis and other pathogens. The position is a full-time, fixed-term contract based on site at the University of Birmingham, carrying a salary of zero pounds per annum.

Requirements

Applicants should note the supervisory team for this project includes Professor Nicholas Loman, Dr Esther Robinson, and Dr Bede Constantinides. The research involves characterising drug resistance across various lineages using existing resistance catalogues and applying genome-wide association methods to study genetic factors related to resistance emergence, pathogenicity, and heteroresistance. Additionally, the student will test whether genome and protein language models can enhance resistance prediction for rare and novel genotypes to address existing gaps in current catalogues.

Key dates

The closing date for applications is 2026-11-23.