Professor Nanzhe Wang at Heriot-Watt University is recruiting PhD students for research in AI-enabled geoenergy and subsurface systems. The research focuses on integrating physics-based modelling and artificial intelligence to address uncertainty quantification, data assimilation, and decision-making in subsurface energy systems. Applications include geological carbon storage, geothermal energy, hydrocarbon reservoirs, and groundwater systems, all of which are critical for supporting the energy transition and achieving net-zero goals.

PhD research topics include hybrid physics–AI modelling and inversion for geoenergy and subsurface flow systems, multi-source and multi-scale data assimilation, digital twins for subsurface energy systems using generative AI and surrogate models, uncertainty-aware decision-making and control for subsurface operations, and active learning for efficient inversion and optimisation. The ideal candidate will have a background in engineering, data science, geoscience, applied mathematics, physics, or computer science, with programming skills in Python, MATLAB, PyTorch, or TensorFlow, and an interest or experience in subsurface systems, geoenergy, and AI/ML.

Funding is available through various external scholarships, including the China Scholarship Council (CSC) for Chinese students, PTDF Overseas Scholarship Scheme (Nigeria), LPDP Overseas Scholarships (Indonesia), Bangabandhu Science & Technology Fellowship Trust (Bangladesh), and other national or industrial sponsorships. Eligible candidates can receive academic support letters for their funding applications. To apply, candidates should email Professor Wang with their CV, academic transcripts, a summary of research interests, and funding status. This opportunity is ideal for students interested in AI, earth science, environmental science, and the application of advanced computational methods to energy and sustainability challenges.