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Embark on a ground-breaking PhD project harnessing the power of Myopic Mean Field Games (MFG) and Multi-Agent Reinforced Learning (MARL) to delve into the dynamic world of evolving cyber-physical
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increasing relevance today due to its ability to bridge the physical, digital, and social domains. CPSS are integral to the modern world, shaping the development of intelligent systems that respond dynamically
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, innovative, inclusive and interactive learning environment. Based at Cranfield University, a global leader in aerospace research, the researcher will be within the Centre for Propulsion and Thermal Power
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learning environment. Based at Cranfield University, a global leader in aerospace research, the researcher will be within the Centre for Propulsion and Thermal Power Engineering which has considerable
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to apply For further information please contact: Name: Dr Francesco Fanicchia Email: Francesco.fanicchia@cranfield.ac.uk If you are eligible to apply for this studentship, please complete
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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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simulations and finite element analysis, with high-heat flux electron beam experiments. The research will simulate and replicate steady, cyclic, and transient thermal loads to better understand PFM behaviour
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opportunities. How to apply For further information please contact: Name: Dr Francis Hassard Email: francis.hassard@cranfield.ac.uk Phone: 00447951810958 If you are eligible to apply for this research
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opportunities. How to apply For further information please contact: Name: Dr Mengwei Sun Email: Mengwei.sun@cranfield.ac.uk Phone:(44) 07594731903 If you are eligible to apply for this studentship, please
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project would suit students with a background in electronics, embedded programming, signal processing, vibration measurement and analysis, maintenance engineering, and electro-mechanical engineering