Lifecycle Optimisation of Wind Farms using Machine-Learning Models Enhanced with Numerical Modelling

This PhD scholarship is offered by the EPSRC Centre for Doctoral Training (CDT) in Offshore Wind Energy Sustainability and Resilience, a partnership between Durham, Hull, Loughborough and Sheffield Universities. The project aims to advance the understanding of wind farm aerodynamics by employing cutting-edge artificial intelligence techniques for modelling and analysis of large wind turbine clusters. The research will integrate granular computing AI methods with spatially informed machine learning techniques, including 2D and 3D convolutional neural networks, to capture relationships between environmental factors and collective aerodynamic behaviour of wind farms. The successful applicant will undertake six months of training with the CDT cohort at the University of Hull before continuing their PhD research at Durham University. The scholarship covers fees plus a stipend currently set at £20,780 per annum at 2025/26 rates, increasing in line with EPSRC guidelines for subsequent years. The 4-year research scholarship includes an intensive taught programme, drawing on expertise and facilities from all four academic partners, supplemented by Continuing Professional Development throughout.