PhD in AI for Low-Carbon Concrete Materials and Structural Design University of Southampton in United Kingdom

PhD opportunity: AI for low-carbon concrete materials and structural design at the University of Southampton, Faculty of Engineering and Physical Sciences.

This project sits at the intersection of civil engineering, materials science, artificial intelligence, machine learning, and structural engineering. The research aims to reduce the carbon footprint of concrete construction by linking concrete composition, mechanical properties, member dimensions, reinforcement, structural performance, and embodied carbon. You will develop AI-assisted models to predict strength and stiffness, connect those predictions to reinforced concrete member behaviour, and use optimisation to search for designs that satisfy engineering requirements while lowering emissions.

The project explores how material choices and structural decisions interact: a lower-carbon mix may require different dimensions or reinforcement to meet load and deformation limits. You will investigate uncertainty in material properties and emission estimates, compare predictions with experimental data and structural calculations, and benchmark results against conventional designs. The outcome is intended to support more sustainable concrete construction and informed engineering decision-making.

Training includes Python, machine learning, concrete mechanics, structural analysis, embodied carbon estimation, optimisation, scientific writing, presentations, and reproducible programming. The project also offers experience relevant to engineering consultancy, construction innovation, and academic careers.

Eligibility: UK 2:1 honours degree or equivalent in civil/structural engineering, materials science, computer science, mathematics, or a related discipline. Essential qualities include interest in AI for concrete and structural design, independent working, clear communication, and teamwork. Desirable experience includes Python/MATLAB, concrete materials, structural analysis, machine learning, numerical modelling, optimisation, carbon assessment, and research writing. English language requirements apply for non-native speakers.

Funding: competition-funded PhD project for students worldwide. Funding routes mentioned include Horizon Europe fee waivers, Presidential Bursaries, and school studentships that may cover UK-level tuition fees and a living stipend for top-ranked applicants. Funding is awarded on a rolling basis, so early application is encouraged.

How to apply: Apply online for Research, 2027/28, Faculty of Engineering and Physical Sciences. Select full-time or part-time, search for PhD Engineering & the Environment (7175), and include the supervisor name in section 2. Submit a cover letter, research proposal, CV, two references, transcripts/certificates, and English language evidence if needed.

Supervisor: Dr Ye Li. Initial questions: [email protected]. Application queries: [email protected].