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The growing demand for high-performance, low-power large-area CMOS technologies has driven interest in a range of new materials, including silicon-based thin films, organic semiconductors, and metal
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the ability to simulate the temperature of the canopy-soil system, they provide valuable information on the interactions with the underlying surface. This is particularly important for urban areas where sparse
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Are you passionate about artificial intelligence, data analytics, and cutting-edge engineering applications? Join our interdisciplinary research team and contribute to the future of Non-Destructive
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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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landscape, from SMEs and start-ups to OEMs and large-scale global manufacturers. For more information please visit the MTC website . Contact For further information on this PhD position please contact Dr
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Assistants is £32,546 - £35,116 and for Research Associates this is £37,174 - £45,413 per annum. Suitable candidates should have previous experience of genetic analysis of large scale genome sequence data and
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) Applications are invited for a 3.5-year STFC funded PhD studentship. The studentship will start on 1st October 2025, subject to confirmation by STFC. Project Description The QCD theory describes the interaction
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Applications are invited for a fully funded, full-time PhD studentship in the Department of Mechanical and Aerospace Engineering, supported by Vestas Technology (UK) Ltd, one of the largest wind
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., StableDiffusion) and large language models (LLMs) based on the transformer architecture [6] (e.g., ChatGPT). In general, the above generative models need considerable amount of computational resources in terms
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or sensor arrays. Experience generating, processing and analysing large material property datasets including correlating between multiple techniques, or developing computational reconstruction techniques