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group have developed an AI-enabled system which can extract detailed retinal vasculometry characteristics from colour fundus photographs (CFPs) in a fully automated way, allowing application to large
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into electric propulsion systems, composite materials, and advanced simulation technologies. Vision We are seeking a highly motivated PhD student to join our interdisciplinary team to help address critical
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. Specific requirements of the candidate Essential Skills: A background in chemistry, physics, materials science, engineering or related fields. Enthusiasm for multidisciplinary research and problem-solving
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both the fundamental physics of electromagnetic materials and practical applications in 6G communications. The PhD is 4 years and funded by DSTL (Defence Science and Technology Laboratory), and you will
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(or equivalent) in: Engineering (Mechanical, Materials, or related disciplines) Physics, Chemistry, or Applied Mathematics About the Leonardo Centre:www.sheffield.ac.uk/leonardocentre The Leonardo Centre at the
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the successful and vibrant UK catalysis and central facilities communities, whilst building skills in inorganic and physical chemistry, applied and sustainable catalysis and advanced X-ray characterisation
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team bridging aerospace and materials research, with access to high-performance computing resources and the university’s state-of-the-art materials research facilities, including high-resolution X-ray CT
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of the brain, caused by a virus, an infection, or an autoimmune response. Following encephalitis, children and young people can experience physical/neurological consequences (e.g., headaches, seizures, sleep
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predictive accuracy and prohibitively long computational times, making them unsuitable for real-time process control. Artificial intelligence (AI) models present a promising alternative by addressing
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recruitment strategies for a novel prostate cancer screening study. Prostate cancer is the second commonest cause of cancer death in men in the UK. Currently there is no NHS screening programme, with men