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AI design of ultrathin lenses for compact imaging devices The Faculty of Engineering at the University of Nottingham is seeking an enthusiastic, self-motivated student who enjoys working as part of
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AI design of ultrathin lenses for compact imaging devices The Faculty of Engineering at the University of Nottingham is seeking an enthusiastic, self-motivated student who enjoys working as part of
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to the analysis of time series. In particular, the project will examine and develop methods that go beyond the Markovian paradigm. It will consider a range of time series data, focusing on those that show
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at the Biodiscovery Institute at UoN, a multidisciplinary centre with advanced laboratory and imaging facilities Access to a full range of equipment and laboratory facilities. Inclusive and supportive lab culture with
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to produce anti-counterfeit markings, dye-free colour images, humidity and chemical sensors, anti-glare coatings and optical filters. This project will develop additive manufacturing of devices with actively
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. cell culture, molecular biology, imaging, cell signalling assays). As well as performing experiments on the project, the role will involve providing training in techniques to relevant staff/students
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Environment: Based at the Biodiscovery Institute at UoN, a multidisciplinary centre with advanced laboratory and imaging facilities Access to a full range of equipment and laboratory facilities. Inclusive and
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Research Groups at the Faculty of Engineering, which conduct cutting-edge research into electric propulsion systems, composite materials, and advanced simulation technologies. Vision We are seeking a highly
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and a construction and testing capability up to 5MW Vision This project aims to leverage the electric propulsion hardware developed in the EU-funded €40M NEWBORN – “NExt generation high poWer fuel cells
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key area of patient safety that can be improved with the use of computer vision approaches to system analysis. For many clinical procedures there can be multiple deviations in service delivery, which