PhD Studentship: Explainable Predictive AI Models for Environmental Impact of Offshore Wind Farms

Supervisor(s)

• 1) Dr Xinhui Ma, University of Hull 
• 2) Dr Koorosh Aslansefat, University of Hull
• 3) Prof Nina Dethlefs, Loughborough University)

Enquiries email: xinhui.ma@hull.ac.uk 

This PhD scholarship is offered by the EPSRC CDT in Offshore Wind Energy Sustainability and Resilience; a partnership between the Universities of Durham, Hull, Loughborough and Sheffield. The successful applicant will undertake six-month of training with the rest of the CDT cohort at the University of Hull before continuing their PhD research at Hull.

Offshore wind is vital to the UK’s transition to net zero, but as the industry scales, understanding and managing its environmental and socio-economic impacts becomes increasingly important. This PhD will develop explainable predictive AI models to assess and forecast how offshore wind farms influence marine ecosystems, seabed mobility, and local industries such as fishing.

Unlike traditional “black-box” AI, these models will focus on explainability, ensuring that predictions are transparent and trustworthy for regulators, developers, and local communities. The research will integrate diverse datasets from ecological monitoring, geospatial surveys, and socio-economic sources (including DEFRA and MMO datasets) to build models that capture both environmental and human dimensions of offshore wind.

By combining machine learning with physics-informed modelling, the project will deliver predictive tools that remain consistent with scientific principles while being interpretable to non-specialists. This will allow stakeholders to better anticipate biodiversity changes, manage seabed risks, and understand socio-economic trade-offs.

The student will join a dynamic research environment at Hull and Loughborough Universities, working closely with other PhDs in the cluster on sustainable offshore wind. They will also engage with industry partners and policymakers, ensuring that research outputs have direct real-world impact.

Training and development

You will benefit from a taught programme, giving you a broad understanding of the breadth and depth of current and emerging offshore wind sector needs. This begins with an intensive six-month programme at the University of Hull for the new student intake, drawing on the expertise and facilities of all four academic partners. It is supplemented by Continuing Professional Development (CPD), which is embedded throughout your 4-year research scholarship.

The successful candidate will gain cutting-edge expertise in AI, sustainability, and stakeholder engagement—skills that are in high demand in both academia and industry.

Eligibility requirements

If you have received a First-class Honours degree, or a 2:1 Honours degree and a Masters, or a Distinction at Masters level with any undergraduate degree (or the international equivalents) in Computer Science, Data Science, Mathematics and Statistics, or related quantitative disciplines, with strong skills in programming and machine learning, we would like to hear from you. Experience or interest in environmental science and sustainability will be highly advantageous.

If your first language is not English, or you require Tier 4 student visa to study, you will be required to provide evidence of your English language proficiency level that meets the requirements of the Aura CDT’s academic partners. This course requires academic IELTS 7.0 overall, with no less than 6.0 in each skill.

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