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14th September 2025 Languages English English English The Department of Electronic Systems has a vacancy for a PhD Candidate in Wind Turbine Noise Prediction in the Norwegian Context Apply
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Dynamics (FLOW), there is now a vacancy for a PhD research position starting 1 October 2025. At FLOW, we have unique expertise in the study of paired vertical-axis wind turbines, combining experimental
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of Strathclyde will lead the wind energy training and research elements of the programme. Funded by EPSRC, this 4 year PhD studentship, at the University of Strathclyde is in the area of novel wind turbine concept
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potential around the UK and Ireland. This PhD project aims to develop and assess the feasibility of various novel fixed-bottom solutions for deep-water wind turbine deployment from structural and economic
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offshore wind OEM—invites applications for a fully funded PhD position on the “Development and Implementation of an Autonomous Decision Support System for Optimized Maintenance in Wind Turbine Infrastructure
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to integrate floating offshore wind turbines and wave energy converters to capture wind and wave energy. The hybrid system’s dynamic responses will be investigated and advanced vibration control technologies
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of floating offshore wind turbines with sustainable concrete floaters. The role is for the second intake of the EnerHy programme which commences in October 2025. Research project overview: To achieve
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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
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-house database of experimental real-world data enabling large-scale validation of developed algorithms. Wind turbine drivetrains are critical components, and their failures can lead to significant
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used in wind turbine blades, structural engineering exposed to offshore environments. However, the rapid growth of the wind turbine industry is expected to generate million tons of blade waste globally