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Advanced Wind Turbine Technology for Urban Environments Department of Mechanical Engineering PhD Research Project Self Funded Prof M Pourkashanian, Prof L Ma, Prof Derek Ingham Application
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project aims to bridge key gaps in wind energy optimization by integrating digital twin technology with advanced machine learning. It involves developing a holistic digital twin model that incorporates
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the development of offshore wind energy and have a passion for geotechnical engineering? This PhD position is for you. This project is a unique opportunity to contribute to the advancement of sustainable energy
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Settlement status) with a first class, or strong upper second-class honours degree in Mechanical/Civil/Materials/Marine/Structural Engineering. International students are welcome to apply provided
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-settled status. The successful candidate will have: a first-class degree in Engineering, Maths or Physics; strong programming ability in at least one of C++, Fortran or Python; demonstratable skills in
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CFD Study of Wind Turbine Aerodynamics Department of Mechanical Engineering PhD Research Project Self Funded Prof M Pourkashanian, Prof L Ma, Prof Derek Ingham Application Deadline: Applications
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Investigation of white etching crack damage mechanism in wind turbine gearbox bearings Department of Mechanical Engineering PhD Research Project Self Funded Prof H Long Application Deadline
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Damage characterisation and root cause analysis of wind turbine pitch bearings Department of Mechanical Engineering PhD Research Project Self Funded Prof H Long Application Deadline: Applications
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Adjoint based optimization of vertical axis wind turbines Department of Mechanical Engineering PhD Research Project Self Funded Prof L Ma, Prof M Pourkashanian, Prof Derek Ingham, Dr Ava
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Advanced Wind Turbine Control Systems Department of Mechanical Engineering PhD Research Project Self Funded Prof M Pourkashanian, Prof L Ma, Prof Derek Ingham Application Deadline: Applications