PhD Studentship: Computational Identification of Genomic Threats Pathogenetic Bacteria Using Machine Learning

Infectious diseases present a significant threat to the health of the UK population and economy, accounting for 1 in every 14 deaths and with overall annual costs estimated at £30bn each year. Bacterial infections form a key part of this threat, made even more concerning by the rapidly growing numbers of pathogenic bacteria resistant to antibiotics. As part of the response of this threat, the international scientific community both collects key bacterial strains and sequences their genomes. This enables the analysis of these genomes to determine genes and genomic structures that are implicated in infection processes and antimicrobial resistance.

The fast-growing quantities of genomic data require new computational approaches with which to perform these analyses. This project aims to combine established methodologies within phylogenetic analysis – the building of evolutionary trees – and machine learning algorithms to develop new approaches and related software tools to better understand associations between bacterial genes and functions such as resistance to antibiotics, helping us to make sense of the new genomic datasets.

The successful candidate will have the opportunity to develop skills in cutting edge computational techniques from leading experts in three UK institutions (the University of East Anglia, the UK Health Security Agency and the Earlham Institute), providing a rich training environment. The three institutions are further embedded within national and international networks of collaborating scientists, presenting numerous opportunities for skill and knowledge development. The software developed by the candidate has the potential to feed into emerging public health surveillance systems essential in a post-COVID era. 

A computer science background and skills in programming, machine learning and/or software development would be advantageous. Students with interests in computational biology are particularly encouraged to apply.

Primary supervisor: Vincent Moulton (v.moulton@uea.ac.uk)

Start date: October 2023

For more information on this project, please visit www.uea.ac.uk

Entry requirements: Acceptable first degree in Computer Science

This PhD project is in a competition for studentships allocated to the School of Computing Sciences as a direct result is increased PGT student fee income for the MSc Courses in Cyber Security, Data Science and Computing Sciences.  All successful candidates will be expected to support PGT Lab sessions from October 2023 and related activities as allocated in support of these programmes within the working hours permitted for full-time Postgraduate Researchers.

Funding comprises ‘home’ tuition fees and an annual stipend (2022/23 rate is £17,668, 2023/24 tbc) for a maximum of 3 years.

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