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The project: The deployment of generative AI—particularly Large Language Models (LLMs) based on transformer architectures—in industrial settings poses several critical challenges. Ensuring reliable
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. The enhanced image quality will support earlier and more reliable detection of eye diseases. Combining artificial intelligence with mathematical modelling, this non-invasive, cost-effective approach has
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PhD Studentship: Carbon Nanotube (CNT) Winding Development for Electric Motors The Manufacturing Technology Centre UK, and University of Nottingham This project offers an exciting opportunity
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the development of new tools for coupled oscillator theory in time-delayed systems of differential equations. The resulting models will be analysed with analytical tools from applied mathematics and numerical
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braiding platform, the PhD work will pave the way for next-generation ultra-high speed propulsion systems. The student will receive full training and support in both modelling and experiments. The skills
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to date focus on just one layer, understanding what keeps AF going is challenging. This PhD project aims to bridge that gap by combining advanced machine learning tools with a new experimental protocol
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manufacturing processes. This is posing major environmental and ethical challenges. The project will motivate the PhD student to develop next generation electric motors with advanced CNT windings, a promising
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on subjective human judgements or assessments by other AI models, offering no formal guarantees of alignment---raising concerns about trust, especially when these technologies are deployed in real-world scenarios
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No of positions: 1 This 3.5 year PhD project is fully funded at UK rates; the successful candidate will receive a tax free stipend set at the UKRI rate (£20,780 for 2025/26) and tuition fees will be
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Exciting Fully Funded PhD: Computational Modelling for High-Pressure, Low-Carbon Storage Technologies. Be a Key Player in Shaping the Future of Clean Energy Storage! School of Mechanical, Aerospace