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include doped oxides or composites engineered to enhance ionic mobility while suppressing electronic conductivity. A key objective will be to understand the relationships between chemical composition
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of mill and production operations. The scientific challenge will be to use the model and machine learning alongside live mill data (temperature, rolling loads etc) to reverse engineer the current
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) are widely used in industries such as automotive and electrical engineering. During service, these materials are frequently exposed to harsh environments involving elevated temperatures, oxygen, and moisture
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-convex optimisation, performance analysis, machine learning, etc.) 1) Applicants should have, or expect to achieve, at least a master’s (or international equivalent) in a relevant science or engineering
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, filtration, detention, conscription, the transfer of children, exploitation under conditions of engineered deprivation) that is rarely analysed as a single phenomenon, and rarely analysed as slavery. Working
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challenge is enabling high-level reasoning for long-horizon tasks without compromising the speed, reliability and efficiency required for real deployment. Current systems often reason effectively but act
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advanced experimental studies conducted within the Department of Chemical Engineering at the University of Manchester and at the Diamond Light Source. In addition, the successful applicant will undertake
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that extend beyond current capabilities. Potential targets include queues, deques, priority structures, linked structures, and new DNA-native information architectures capable of operating in vitro or in living
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research group drawn from a range of backgrounds including chemistry, molecular biology and chemical engineering. They will receive a broad scientific training across these areas, as appropriate
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/EPSRC Energy Transfer Technology Skills and Training (S&T) Hub. The main aim of the S&T Hub is to train the next generation of leaders in energy transfer technologies relevant for defence and other