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difficult for industry to predict and control product performance. This PhD project will tackle that challenge by applying advanced polymer characterisation techniques to better understand and quantify
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supporting the Net Zero 2050 target. This PhD project will develop an AI-enabled framework that optimizes wind turbine control and predictive maintenance. Using Deep Reinforcement Learning (DRL), the system
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into advanced turbofan configurations. This doctorate will research highly innovative technologies that carefully control the temperature of key engine components. The Oxford Thermofluids Institute
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Failure Analysis of Composite Sleeves for Surface Permanent Magnet Electrical Machines This exciting opportunity is based within the Power Electronics, Machines and Control (PEMC) and Composites
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This exciting opportunity is based within the Power Electronics, Machines and Control (PEMC) and Composites Research Groups at the Faculty of Engineering, which conduct cutting-edge research
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This PhD project will develop next-generation grid-scale energy storage solutions integrated into HVDC (High Voltage Direct Current) systems at the University of Edinburgh, in partnership with UK
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Applications are invited for a PhD project within the University of Nottingham’s Faculty of Engineering, in the Centre for Additive Manufacturing research group (CfAM). The student will work in
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PhD project: 3D-Printing Devices with Responsive Structural Colour Applications are invited for a PhD project within the University of Nottingham’s Faculty of Engineering, in the Centre for Additive
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to discuss the post informally, please contact Dr Yuanchang Liu () About you The ideal candidate will hold a PhD (or be close to completion) in Mechanical Engineering, Robotics, Marine Engineering, or a
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the technology, hence there is a drive from the industry to address this. To answer this question requires an interdisciplinarity approach, combining Industry input alongside physical sciences and physiological