We are recruiting a PhD student to join an interdisciplinary project at the interface of computational modelling, artificial intelligence, environmental science, and antimicrobial resistance (AMR).
Microplastics are increasingly recognised as "Trojan horses" for environmental pollutants, concentrating antibiotics and facilitating their movement through aquatic ecosystems. However, little is known about how microbial processing alters antibiotic–microplastic interactions and influences environmental persistence, pollutant transfer, and AMR risk.
This project will combine:
The student will investigate how antibiotic binding to environmentally relevant polymers changes following biological processing within microbial food webs, generating new mechanistic insights into the links between plastic pollution and antimicrobial resistance.
A key feature of the project is a collaboration with DeepMirror, a London-based AI company specialising in molecular representation learning, generative chemistry, and AI-driven molecular design. The successful candidate will benefit from direct industry engagement, access to AI-driven discovery workflows, and a dedicated industry placement during the PhD.
The supervisory team brings together expertise in environmental science, computational chemistry, molecular simulation, and machine learning:
The project is funded through the EngBio4Env Doctoral Focal Award, a UKRI-supported doctoral training programme focused on engineering biology solutions to major environmental challenges.
Further information and application details can be found here.
Informal enquiries are strongly encouraged. Prospective applicants are welcome to contact either:
Dr Julia Reiss – Julia.Reiss@brunel.ac.uk
Dr Michelle Sahai – Michelle.Sahai@brunel.ac.uk
Application Deadline: 20 July 2026 for September 2026 entry
