Postgraduate research project

AI-assisted design of intelligent antimicrobials for gastrointestinal disease treatment

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

This project aims to develop AI-driven, metal-based smart antimicrobials targeting gastrointestinal infections and antimicrobial resistance. You will use cutting-edge AI drug design and microfluidic organ-on-a-chip technology for rapid, animal-free drug screening. 

This project offers an exciting opportunity to develop next-generation antimicrobial therapies to tackle gastrointestinal bacterial infections and the growing global challenge of antimicrobial resistance (AMR). You will focus on designing novel metal-based antimicrobial agents using artificial intelligence (AI)-assisted drug design techniques. These computational methods enable rapid molecular screening and structural optimization, accelerating the discovery of potent and selective therapeutics.

To test drug efficacy and safety, you will employ advanced microfluidic organ-on-a-chip models, miniaturized, biomimetic systems that replicate the human stomach environment in vitro without the need for animal testing. This innovative approach provides a more ethical, cost-effective, and physiologically relevant platform for drug evaluation.

Through this project, you will gain multidisciplinary expertise in AI-driven drug discovery, bioinorganic chemistry, microfluidics, and disease modelling. You will collaborate with experts in pharmaceutical sciences, materials engineering, and computational biology, working at the cutting edge of infectious disease research.

The project aims to produce new antimicrobial candidates with improved efficacy against resistant gastrointestinal pathogens and to pioneer platforms that streamline preclinical drug testing. This work has the potential to significantly impact global health by addressing critical treatment gaps and reducing reliance on animal models.