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Adaptive AI for Wind Control and Predictive Maintenance PhD at Cranfield University 2026

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This fully funded PhD studentship, sponsored by the EPSRC Doctoral Landscape Awards (DLA) and RES Group, offers a bursary of £25,000 per annum, covering full tuition fees. The project focuses on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands-on experience with real-world SCADA data, industry collaboration with RES Group, and training in high-fidelity simulation environments (OpenFAST, Digital Twin technology). This opportunity is ideal for those interested in renewable energy, AI for energy systems, and wind turbine engineering.

Table of Content

Summary

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Benefits

Fully funded PhD studentship

Requirements

  • Applicants should have a first or second class UK honours degree or an equivalent in a discipline related to electrical engineering, energy, or computer science.
  • The ideal candidate should have a background of electrical and computer and have strong programming experiences for wind turbines.
  • The candidate should be self-motivated, possess good communication skills for regular interaction with other stakeholders, with a passion for industrial research.

Check also:
Wits-Edinburgh Programme in Sustainable African Futures by Mastercard Foundation 2026-2027
Department of Aeronautics MSc Scholarship at Imperial College London 2026

Application Deadline

October 1, 2025

How To Apply

Are you qualified and interested in this opportunity? Kindly go to Cranfield University on eve.cranfield.ac.uk to apply
  • Reference number - SATM599

For more details, visit Cranfield University scholarship webpage

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