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Field
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, which are essential for safe operation in these challenging aerospace environments. You will develop robust, physics-based models to analyse failure, with a focus on understanding mechanical and
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analytics tools have been massively developed in the research community to address this challenge. These AI-based analytics tools are data-driven and black-box, so the interpretation of how predictions
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of complex, dynamic flows relevant to closely coupled engine aircraft configurations. You’ll join a pioneering multidisciplinary team that values equity, diversity, and inclusion, gaining unique expertise in
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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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satellites, with the potential for travel to test instrumentation in ideal locations. Additionally, the simulation work will focus on developing computational models to validate instrumentation and optimising
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the impacts of intermittent discharges, such as sewage overflow (SO) spills on our natural watercourses. This cutting-edge research will look at how to engineer these green technologies to maximise
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is desirable. This interdisciplinary project is suited for students who wish to gain expertise in both human health and data-driven biology. Please contact Dr Irina Chelysheva (i.chelysheva
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. The developed technology will be rooted in causal reasoning, and we envision leveraging causal generative AI methods to develop a rigorous and comprehensive AI testbed. Clinical applications include, but are not
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challenges in quantum technology adoption stem from the lack of standardized benchmarking methods and the inherent difficulty in validating quantum devices beyond classical simulation capabilities. Recent
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the areas of innovation management, the creation and growth of technology-intensive organisations, business analytics, and entrepreneurship. The research undertaken at the UCL School of Management has been