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PhD in AI-Driven Protein Engineering, Enzymology, and Structural Biology of Peptidase vs Ligase Activity University of Bath in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
4-year fully funded PhD studentship supported by the SWBio DTP Hub Doctoral Training Partnership.
Deadline
Dec 2, 2026
Country
United Kingdom
University
University of Bath

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About this position
PhD opportunity at the University of Bath in the Faculty of Science, starting September 2027.
This interdisciplinary project sits at the interface of artificial intelligence, protein engineering, enzymology, and structural biology. The research will investigate why closely related enzymes in the same family act either as peptidases (peptide-cutting proteases) or ligases (peptide-joining enzymes). The project combines AI-driven protein analysis, directed enzyme evolution, biochemical characterisation, and structural biology to uncover the molecular rules that determine catalytic outcome.
The student will collaborate with researchers at the University of Bath and the University of Exeter, and the work aims to build predictive frameworks for engineering next-generation peptide ligases with applications in biotechnology, synthetic biology, and drug discovery.
Funding is fully funded for 4 years through the SWBio DTP Hub Doctoral Training Partnership.
Deadline: midday (GMT) on 2 December.
Interested applicants should review the full advert on the SWBio website and apply for project 3535.
Funding details
4-year fully funded PhD studentship supported by the SWBio DTP Hub Doctoral Training Partnership.
What's required
Applicants should be interested in combining artificial intelligence, protein engineering, enzymology, and structural biology. The project is interdisciplinary and involves AI-driven protein analysis, directed enzyme evolution, biochemical characterisation, and structural biology. No specific degree, GPA, or language-test requirements are stated in the post.
How to apply
Visit the SWBio website to read the full advert and submit an application through the project page. Use project number 3535 when searching for the opportunity. Apply before midday GMT on 2 December.
More information can be found here
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