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building typologies. This research aims to transform Pulse testing through AI integration—specifically leveraging descriptive, predictive, and generative modelling techniques—to enhance test accuracy
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pursuing impactful research in a relevant area. Successful applicants will benefit from supervision by experienced and research-active faculty members, access to dedicated doctoral training, development
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building physics and artificial intelligence. The student will have access to research facilities within the Department of Architecture and Built Environment and the School of Computer Science. They will
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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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of Nottingham, EPSRC and industry) will provide a multi-disciplinary approach to training researchers in new technologies that can significantly improve the incorporation of solar farms into future sustainable
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underpinnings of surface formation. The student will join an interdisciplinary research group with a broad interest in plant biomechanics, ecology, development and evolution. The supervisory team comprises plant
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provide real-world insights and infected sample sets for testing. Student will join an enthusiastic, friendly, and supportive group of researchers who are all working on various analytical and experimental
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This exciting opportunity is based within the Power Electronics and Machines Centre (PEMC) Research Group at Faculty of Engineering which conducts cutting edge research into enabling technologies
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students and post-doctoral researchers using high performance computing to advance understanding of high-speed aerodynamics. Over the past decade we have developed efficient open-source software that enables
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PhD Studentship Aircraft Electrical Power System Stability This exciting opportunity is based within the Power Electronics and Machines Centre (PEMC) Research Group at Faculty of Engineering which