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Field
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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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increase healthcare access. Further, such technologies can facilitate remote training monitoring and performance enhancement for athletes. Developing accurate, low-cost, comfortable technologies
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This PhD studentship is a part of Rolls-Royce sponsored research centre developing advanced control systems to enhance the performance and efficiency of new aerospace propulsion systems. We apply a
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, balancing efficiency and sustainability in AI deployment poses a significant challenge, calling for advances in model design and training to reduce environmental impact while maintaining high performance
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how variations in mould structure, porosity, and surface characteristics affect radiative heat transfer and casting performance. Phase-field modelling will also be used to simulate defect formation and
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Research Group at the Faculty of Engineering which conducts cutting edge research into experimental and computational heat and mass transfer, multiphase flows, thermal management, refrigeration, energy
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University of Strathclyde will lead the wind energy training and research elements of the programme. Funded by ESB and EPSRC, this 4 year this PhD studentship, at the University of Strathclyde is in the area
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members of staff. Research in the Department is organised into six themes : Causality; Computational Statistics and Machine Learning; Economics, Finance and Business; Environmental Statistics; Probability
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. This PhD project investigates how emerging Next-Generation Networks (NGNs), including Beyond-5G (B5G) and 6G, can be connected to ensure secure, high-performance mission-critical communications, vital
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Worldwide Dr Marco Colombo Application Deadline: 30 September 2025 Details Are you ready to shape the next generation of high-performance engineering systems? Join a cutting-edge, fully-funded PhD project