The London School of Hygiene & Tropical Medicine is a world-leading centre for research and postgraduate education in public and global health. Our mission is to improve health and health equity in the UK and worldwide; working in partnership to achieve excellence in public and global health research, education and translation of knowledge into policy and practice.
We are seeking to appoint a Research Fellow to apply machine learning and artificial intelligence techniques to develop an AI-powered solution to help pre-empt the impact of drug resistance mutations and aid in the combat of the growing threat of antimicrobial resistance (AMR).
This exciting post is funded by the Biotechnology and Biological Sciences Research Council (BBSRC) and is directed by Dr. Nicholas Furnham in collaboration with Prof. Kat Holt at LSHTM. It is an international partnership project in collaboration with Prof. David Ascher’s groups at the University of Queensland and Baker Institute in Melbourne (Australia).
Drugs against infectious diseases have transformed human and animal health and saved millions of lives. Nevertheless, their widespread use and misuse has led to the emergence of AMR that poses a potentially catastrophic threat to public health and animal husbandry. By modelling how pathogens mutate to avoid the effect of drugs, we can better predict how infections will respond to specific drugs and may be able to design drugs that have longer clinical use. As well as directly benefiting those working to develop the next generation of drugs, it also benefits those managing prescribing routines and in surveillance, identifying new emerging resistance that can be acted on before it becomes widespread within a population.
The successful applicant will develop a Large Language Model (LLM)-based tool for predicting mutations causing resistance trained on features derived from large collections of pathogen genome data. The model will be validated and applied to specific pathogens including Mycobacterium tuberculosis, Salmonella Typhi and Klebsiella pneumoniae (WHO priority pathogens). As an international partnerships project, the post holder will be involved in knowledge exchange with our partner labs in Australia, including a period embedded in their group, as well as UK based workshops to enhance the collaborative network.
Applicants should have a postagraduate degree, ideally a doctoral degree, in a relevant topic, relevant experience in bioinformatics, computational biology or machine learning, proven ability to work independently, as well as collaboratively as part of a research team, and proven ability to meet research deadlines. Further particulars are included in the job description.
The post is full-time and funded by the UK Biotechnology and Biological Sciences Research Council until 13 August 2025 (with a possibility of an extension). The salary will be on the Academic Grade 6 scale in the range £43,947 - £49,908 per annum (inclusive of London Weighting). The post is based in London.
The post will be subject to the LSHTM terms and conditions of service. Annual leave entitlement is 30 working days per year, pro rata for part time staff. In addition to this there are discretionary “Wellbeing Days”. Membership of the Pension Scheme is available.
Applications should be made online by clicking the 'Apply' button above. Online applications will be accepted by the automated system until 10pm on the closing date. Any queries regarding the application process may be addressed to [email protected] .
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