Although bacteriophage can combat many bacterial diseases, they constitute an under-utilised resource because most species remain unidentified. Bacteriophage offer great hope for future “One Health” treatment options, provided the groundwork is done to establish their identities via host infection. However, traditional experimental laboratory methods for bacteriophage identification are slow and labour-intensive. With predictions of health issues soon to rise sharply due to increasing antimicrobial resistance, both in humans and animals, novel high-throughout computational tools for bacteriophage identification are needed. This project will explore bacteriophage applications to improve animal health in the poultry industry, a critical commercial sector in the UK agri-food system.

As this project is fully interdisciplinary, you will apply a combination of computational methods and experimental techniques. You will first use classical computational sequence-based tools from bioinformatics to identify bacteriophage DNA from previously collected poultry samples. Then, you will develop novel AI-based computational methods for bacteriophage identification (e.g., taxonomic labelling) and characterisation (such as functional gene identification). These computational tasks, carried out at the University of Strathclyde, will constitute most of the project. Then, the student will apply gold-standard experimental techniques at Queen’s University Belfast and Agri-Food and Biosciences Institute, to isolate bacteriophage and screen their potential bacterial hosts/targets.

The appointed student will receive cross-disciplinary training in machine learning, software development, avian virology and molecular microbiology. They will start on the project by learning how to use and develop computational methods involving cutting-edge deep learning techniques, such as large nucleotide/protein sequence models. Later in the project, they will work closely with stakeholders in the field, from microbiologists to veterinarians in the UK and international poultry sector. They will emerge with cutting-edge skills and experiences in deep learning, computational biology, and microbiology, which are all in strong demand in academia, as well as in the public and private sectors.

Further information

This 4-year PhD programme is under the UKRI AI Centre for Doctoral Training in Sustainable Understandable agri-food Systems Transformed by Artificial Intelligence (SUSTAIN). SUSTAIN is a collaboration between the Universities of Lincoln, Aberdeen, Queen’s Belfast and Strathclyde, and focuses on the application of Artificial Intelligence (AI) to sustainable agri-food. Academic staff and partners have co-created projects based on key industry challenges, which will be shaped with your input during the first year of your PhD. 

All projects will benefit from external partner involvement. Recruitment is being co-ordinated by the University of Lincoln. 

Shortlisting will take place week commencing 27 October, with interviews taking place online between 12 November and 1 December. Candidates will be informed week commencing 1 December. Thereafter, the successful candidate will then complete and submit their application to the University of Strathclyde.