Skip to main content

Postgraduate research project

AI-guided phage engineering for clinical care in military operations

Funding
Competition funded View fees and funding
Type of degree
Doctor of Philosophy
Entry requirements
2:1 honours degree View full entry requirements
Faculty graduate school
Faculty of Engineering and Physical Sciences
Closing date

About the project

Leveraging AI to design viruses that kill drug-resistant bacteria. This PhD will develop synthetic bacteriophages targeting multidrug-resistant pathogens associated with conflict and military healthcare. Combining AI, genomics, synthetic biology and microbiology, the project will build an iterative design–build–test–learn platform to rapidly develop and experimentally validate new approaches to tackling antimicrobial resistance.

Antimicrobial resistance (AMR) is a major challenge in conflict and military healthcare, where trauma, disrupted healthcare and sanitation, and difficulties implementing infection prevention and control can promote the emergence and transmission of multidrug-resistant organisms (MDROs). Yet there is relatively little known about the diversity and genomic characteristics of MDROs circulating in these settings, or how best to target them.

Bacteriophages are viruses that specifically infect bacteria, and have been proposed as alternatives to antibiotics for treating drug-resistant infections. However, their strain specificity makes identifying effective phages and phage cocktails challenging. Recent advances in AI generative genome language models have demonstrated that complete, viable bacteriophage genomes can be designed computationally, creating an opportunity to develop phages tailored to clinically important drug-resistant bacteria.

This PhD will develop a prototype platform for AI-guided design of synthetic phages targeting priority MDROs, including Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacterales and Staphylococcus aureus. You will combine environmental surveillance and bacterial genomics with AI-assisted phage design, genome synthesis and experimental phage susceptibility testing. Results from experimentally characterised phages will feed back into computational models, establishing an iterative design–build–test–learn cycle for improving phage design.

The project offers interdisciplinary training spanning epidemiology, AI, comparative genomics, synthetic biology, phage biology and laboratory microbiology across academic and government partners, including the military, Southampton, Oxford, UKHSA and DSTL, and with biotechnology expertise from NEB, including two three-month placements at NEB headquarters in Massachusetts, USA.