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. Programming, coding, and experimental hardware skills (desirable). Strong analytical and mathematical capabilities. A passion for research and a willingness to learn. Excellent presentation, communication, and
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individual expressive behaviours. The project builds on recent work showing that person-specific cognition can be computationally approximated by learning personalised neural architectures or model weights
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collaboration. The successful candidate will work alongside an active research group specialising in AI, blockchain, federated learning, trust frameworks, and intelligent systems. This fully funded studentship in
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/coding and experimental hardware skills are desirable. Strong analytical and mathematical skills. Passion for research and willingness to learn. Good presentation, communication and scientific writing
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environments where terrain can change abruptly. However, formally certifying these opaque learning-based components demands impractical resources, presenting critical safety assurance challenges and delaying
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. This project proposes the development of a new CFD simulator for offshore renewable energy applications based on physics-informed deep learning that offers greater efficiency and robustness. This is a unique and
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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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be a game changer. Deep learning models can learn the mapping between material states and ultrasonic responses from simulation data, delivering quantitative predictions once trained, and remarkably
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, a strong degree in computer science, cybersecurity, mathematics, or a related subject. Experience with cryptography, machine learning, or systems implementation is valuable, as are solid programming
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development, education, organisational change, and community engagement, reflecting a longstanding belief that drama-based learning cultivates capabilities with value across a wide range of contexts. However