Research project to define the most effective approach to TB contact investigations informed by routine whole genome sequencing data

3-year PhD post funded by the Faculty of Medicine

Applications are invited from candidates that hold, or expect to obtain, a first or upper second-class undergraduate degree or UK equivalent in a relevant subject, and a master’s degree in a relevant subject (TB research, mathematical modelling, bioinformatics, genomic analysis) is preferrable, for a 3-year PhD.

The studentship will be funded for 3 years with a tax-free bursary of £18,000 per annum plus Tuition fees, at the rate applicable to UK Home students. Suitably qualified students non-eligible for home tuition fees are welcome to apply but will be responsible for paying the difference between the home and overseas fee rates. Eligibility criteria for home tuition are outlined here on the fee status page.

Summary of Research

In recognition of the importance of tuberculosis (TB) as a major global health challenge, the World Health Organisation has set ambitious targets for the elimination of this disease. In low TB incidence settings such as the UK, contact tracing plays a critical role in efforts towards elimination. Contact tracing aims: (i) to identify and treat cases of active TB amongst contacts as rapidly as possible, in order to limit opportunities for transmission, and (ii) amongst contacts without active TB, but with evidence of latent TB infection, to implement preventive therapy in order to protect against progression to active disease. However, there is a need to understand how best to focus and prioritise contact tracing investigations to achieve incidence reductions in the most cost-effective way possible.

To address this important public health need, this project will bring together data from a diverse range of sources from the UK, including genomic data; social network information; patient data; etc. The project will aim to identify which individuals with TB should be prioritised for contact tracing to identify latent and active TB amongst their contacts. Mathematical modelling will be used in prioritisation strategies and project the potential reductions in TB incidence they could deliver. The student will utilise national UKHSA databases including the enhanced TB surveillance database of all TB notifications and all available genome sequences of M. tuberculosis isolates. Finally, incorporating cost data, this project will then identify cost-effective strategies for contact tracing. In doing so, this project will provide valuable evidence for the TB response in the UK and other low-incidence settings.

This PhD studentship represents a cross-Imperial College PhD collaboration between the NIHR Health Protection Research Unit (HPRU) in Respiratory Infections and the NIHR HPRU in Healthcare Associated Infections and Antimicrobial Resistance. The successful applicant will however be primarily based in NIHR HPRU in Respiratory Infections, St Marys Campus within the National Heart and Lung Institute, which provides an exciting environment, with state of the art facilities and excellent opportunities for PhD student training including research seminars and journal clubs. This project will be carried out in close collaboration with clinical teams embedded in the section, and the institute provides extensive collaborative opportunities with other research groups.

The HPRU is an academic partnership between Imperial College London and the UK Health Security Agency. As such, it will be co-supervised by expert staff at both institutions. The project would ideally suit a student with exceptionally strong background in TB, with experience in data analysis and mathematical modelling and/or pathogen genomics, and with strong interests in developing data-guided strategies for public health action.

Imperial College London provides excellent opportunities for research students' training. All students benefit from a full programme of training in research and transferable skills organised through the Graduate School, the quality of which has been recognised several times at the Times Higher Education (THE) Awards.

How to Apply

Applicants must hold, or expect to obtain, a first or upper second-class undergraduate degree or UK equivalent in a relevant subject, and a master’s degree in a relevant subject (TB research, mathematical modelling, bioinformatics, genomic analysis) is preferrable. To apply please send a CV, a one page personal statement, and the names and addresses of at least two academic referees to Professor Nimalan Arinaminpathy by email on

Please note that candidates must fulfil College admissions criteria.

Application deadline: 15 September, 2022