Advancing molecular risk assessment and risk management of Listeria monocyotogenes in the genomic era.

Listeriosis caused by the bacterium Listeria monocytogenes is the leading cause of death attributed to foodborne disease in England and the EU. There is building evidence that some strains of Listeria monocytogenes are more commonly associated with clinical disease whilst others are more frequently isolated from food and food production environments. Current risk assessment, and risk management strategies employed do not take into account this differential potential to either cause human illness or persist through the food chain.

Public Health England (PHE) have employed enhanced genomic surveillance of Listeria monocytogenes for 5 years and have a wealth of genomic (~4000 isolates) and associated meta-data on source (clinical, food, environment) and where appropriate clinical outcome and exposure. We aim to employ state of the art discovery and predictive methodologies to this data to identify genomic features that are robustly associated with human disease and/or survival in the food chain. This research will facilitate food business operators, risk managers, regulators and public health investigators to integrate molecular risk assessment into the control of Listeria monocytogenes.

This PhD represents a unique opportunity to integrate cutting edge machine learning methodologies into public health surveillance whilst meeting a pressing need for evidence generation for Listeria monocytogenes control. This application of predictive genomics will act as an exemplar providing a robust framework to exploit similar questions in the 100,000 genomes generated as part of infectious disease surveillance within PHE.

We are searching for an enthusiastic PhD student to focus on the analysis of Listeria genome sequences. The studentship is available from the 1st January 2021. Ideally, we are looking for candidates with some bioinformatics experience but that also have an interest in the underlying biology of infectious diseases. We will consider students with a minimum of an upper second-class degree in computing/biology disciplines and/or preferably a Masters degree involving bioinformatics. We consider that this studentship offers a unique opportunity to develop bioinformatics and data analytic skills in an applied area with excellent opportunities for training. Furthermore this studentship will provide a unique exposure to infectious disease surveillance in practice.

This project will be undertaken at Public Health England (Dr Tim Dallman) in association with the University of Warwick (Professor Xavier Didelot). The student will be registered at the University of Warwick.

Please contact Dr Tim Dallman for informal enquiries: [Email Address Removed]

To apply, please send your CV and a covering letter explaining why you are interested in the project and why you are a suitable candidate to: [Email Address Removed]