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-class or 2:1 (or international equivalent) Master’s degree in Computer Science, Robotics, Mechatronics or Electronic/Electrical Engineering, or a related field. • Knowledge of machine learning/deep
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‘Campus’, please select ‘Loughborough’ and select the ‘Programme’ as ‘Mechanical and Manufacturing Engineering’. Please quote the advertised reference number ‘FP-HZ-2025’ in your application under
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-efficiency trade-offs, using automated configuration to find Pareto-optimal designs under real deployment constraints. 2) Build the distributed learning loop. Develop the learning and update mechanisms
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on my prior research on garnet-solid state electrolyte, a membrane with high ionic conductivity, robust mechanical and chemical/electrochemical stability, and affordability, will be explored using
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First-class (or equivalent) degree in Mechanical, Automotive, Powertrain, or Control Engineering, or a closely related discipline. Strong academic performance and research potential are essential
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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functions). Explore model-based RL approaches that integrate learned models with planning and adaptation mechanisms. Hybrid Evolutionary-RL Framework Develop novel frameworks with evolutionary algorithms
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mechanics, and analytical and numerical methods to solve partial differential equations. Excellent oral and written communication skills. Prior experience in computational fluid dynamics or active matter will
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functions). Explore model-based RL approaches that integrate learned models with planning and adaptation mechanisms. Hybrid Evolutionary-RL Framework Develop novel frameworks with evolutionary algorithms
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Antimicrobial resistance is one of the most serious threats to humans in the 21st century. Understanding antimicrobial resistance mechanisms is pivotal for combating superbugs. Pathogens use many