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to perform data work with high accuracy and attention to detail We offer an occupational pension scheme, generous annual leave, hybrid working and excellent training and development opportunities. For further
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diagnostic capabilities. The skills and knowledge gained will be transferable to other applications requiring high-performance radiation detection and advanced material interfaces. Through
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the MMI apparatus, gaining knowledge of, for example, molecular and atomic beams, ultra-high vacuum systems, cryogenic technologies and a range of measurement and surface science techniques. They will also
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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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plants. These advantages include being more compact, lower costs, using single-phase fluid rather than two-phase fluid used in steam turbines, higher cycle efficiency when using low temperature heat
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highly efficient operation. TBCs are crucial to ensure the safe and high-performance operation of such critical parts under extreme temperatures and pressures; however, external contaminants (e.g. Calcium
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., Ni superalloy turbine blades) to ensure a reliable and highly efficient operation. TBCs are crucial to ensure the safe and high-performance operation of such critical parts under extreme temperatures
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operating filters. Quantify operational performance including headloss recovery, filtrate turbidity, biological stability and lifecycle carbon—using high-resolution sensor data and life-cycle assessment tools
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gate drive implementations capable of maintaining reliable switching performance under cryogenic thermal conditions. This project will involve a substantial amount of experimental work using the high
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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