Fully Funded PhD in Generative AI for Resilient Critical Minerals Supply Chains at UCL University College London in United Kingdom

UCL Chemical Engineering and the Sargent Centre for Process Systems Engineering are advertising a fully funded PhD on Generative AI for resilient critical mineral supply chains. The project sits at the intersection of chemical engineering, computer science, industrial engineering, mathematics, and environmental science, with a strong focus on process systems engineering, artificial intelligence, optimization under uncertainty, and supply chain resilience.

The successful PhD candidate will work with Vassilis Charitopoulos and his team at University College London. The research aims to develop a hybrid decision-making framework to study the resilience of critical mineral supply chains under disruption, circularity, and net-zero transition pressures. Planned work includes advanced process and supply chain optimization models, AI-based adversarial analysis of vulnerabilities and recourse actions, and an LLM-based model for scenario analysis and network resilience quantification.

Applicants should have at least a 2:1 degree in engineering or a related discipline. Strong teamwork, communication, and rigorous research skills are expected. Experience with machine learning, optimization algorithms, chemical process simulators such as AspenPlus, and Python is highly desirable.

This opportunity is linked to the UCL EPSRC Landscape Award (UELA) 2026/27, which offers fully funded four-year studentships. Funding includes Home-rate fees, an enhanced stipend of at least £23,466 per year in 2026/27, and a Research Training Support Grant. For Round 2, only Home fee-status candidates can apply. The application deadline is 21 May 2026 at 13:00 UK time.

To apply, use the UELA online forms, complete Parts A, B, and C for the project, and arrange for two referees to submit Part D by the deadline. Successful candidates will later need to complete a UCL admissions portal application.