Miguel Rodrigues

The LASP Lab at University College London (UCL) is inviting applications for a fully funded PhD position in the field of Artificial Intelligence, with a focus on machine learning, optimisation, and scientific modelling. The lab is highly interdisciplinary, working at the intersection of reinforcement learning, black-box optimisation, and generative models for graphs, including advanced topics such as diffusion, flow matching, and connections to fluid dynamics. The main application area is sustainability, and the research will involve building new agents for complex decision-making. The position is supported by a G-Research scholarship, providing four years of funding that covers tuition fees (home rate) and a competitive stipend. Exceptional international candidates may be considered on a case-by-case basis. The successful candidate will also benefit from unique professional development opportunities, including mentorship from G-Research experts, participation in the 'Spring into Quant Finance' programme, annual networking dinners, and opportunities to present at seminars. The project will be supervised by Dr. Laura Toni, with potential co-supervision from Dr. Francesca Boem, Professor Miguel Rodrigues, or Dr. Eduardo Pignatelli, all based in the UCL Department of Electronic & Electrical Engineering. Applicants are encouraged to review the supervisors’ profiles and research outputs and may contact them directly for informal discussions about potential project ideas. Applicants should have a strong academic background in optimisation, mathematics, statistics, and machine learning, with proficiency in Python. A genuine interest in reinforcement learning, graph generative models, or autonomous agents is essential. Candidates should demonstrate strong motivation and the drive to push the boundaries of machine learning theory and applications. Minimum entry requirements for the UCL EEE PhD programme apply, and a letter of support from an academic supervisor is recommended. The initial application deadline is 5 January 2026. To apply, candidates should send their CV (max 2 pages), transcripts, a letter of support, and a short research proposal to Gemma Ludbrook ([email protected]). Early submission is strongly recommended to allow time for discussion and feedback. Selected applicants will be interviewed by the potential primary supervisor and another faculty member, and the top candidate will be invited to submit an institutional PhD application by 6 February 2026. For more information, visit the LASP Lab website and the UCL EEE PhD scholarship page . This opportunity is ideal for highly motivated students interested in advancing the frontiers of AI, machine learning, and scientific modelling in a world-class research environment.