AI-based approach to address drug-resistance in infectious disease

• Funding – self-funded/externally sponsored applicants  (PhD Fees can be found here)
• Applications are accepted year round
• Standard Entry dates – January and September
• Applicants are expected to have a degree (equivalent of Honours or Masters) in a relevant discipline.

Drug resistance is a global problem affecting both public and animal health. In recent years, data on drug efficacy and resistance has increasingly become publicly available. However, an understanding of how structural and biological features (e.g. mutations, gene regulation) are related to the emergence of resistance is still in its infancy. We have recently successfully built machine-learning models predicting drug activity in the Gram-negative bacteria E. coli and P. aeruginosa and linking structural with microbiological features such as efflux pump variants. 

In this project, you will construct models of antimicrobial resistance for animal and human pathogens. You will use molecular modelling and biomolecular simulations to develop a mechanistic understanding of the underlying structure-function relationships and to rationalise the resistance pathways. This work will contribute to the design of improved anti-infectives and to the development of strategies to evade resistance. 

Our research community thrives on the diversity of students and staff which helps to make the University of Dundee a UK university of choice for postgraduate research.  We welcome applications from all talented individuals and are committed to widening access to those who have the ability and potential to benefit from higher education.