PhD Research Opportunity: Unlocking How Agrochemicals Move Through Plant Systems Using Biomimetic Technologies
Imperial College London – Institute of Chemical Biology
London, United Kingdom
This funded PhD studentship offers an exciting interdisciplinary research experience at the interface of plant chemical biology, biomimetic engineering, and data-driven science. Co-sponsored by Imperial College London and Syngenta plc, the project tackles a fundamental challenge in agrochemical science: understanding how molecules travel across the complex internal pathways of plants. Traditional screening methods mainly infer passive movement of chemicals, overlooking active transport processes mediated by plant proteins. This project aims to overcome that gap by building next-generation in-vitro platforms using microfluidic droplet networks and biomimetic membrane systems that replicate plant barrier properties. By embedding plant transport proteins into synthetic membrane interfaces and establishing realistic chemical and electrical gradients, the research will make direct measurements of both active and passive agrochemical translocation. The work integrates advanced tools including automation, robotics, high-resolution imaging and artificial intelligence to support high-throughput screening of agrochemical libraries. The outcomes will drive predictive models that disentangle the physicochemical drivers of uptake from transporter-controlled kinetics, ultimately enabling the design of safer and more selective small-molecule active ingredients with reduced environmental impact.
Eligibility Criteria
Applicants must have UK Home fee status to be eligible for this studentship.
Required Expertise, Skills
The programme will develop a broad range of technical and analytical skills. Training includes microfluidics, plant chemical biology, biomembrane engineering, advanced microscopy, automation and robotics, artificial intelligence and machine learning. Candidates should be prepared for interdisciplinary research that bridges biophysical insight with practical assay development and predictive modelling.
Salary Details
Specific stipend details are not listed on the source page, but the position is described as a funded PhD studentship.
Application Deadline
The application deadline is Wednesday 4 March 2026 at 5 pm.