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) imaging devices (endoscopes) for detecting cancer in hard-to-reach areas of the body, such as the pancreas and ovaries. Background: Cancers deep within the body are notoriously difficult to detect and treat
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(MASI)” involving four UK universities (Nottingham, Cardiff, Cambridge, and Birmingham) and join the Computational Materials Science group led by Prof. Elena Besley (https://ebesley.chem.nottingham.ac.uk
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. What you should have: A 1st degree in physics or engineering. An interest in optics, some ability in computer programming A desire to learn new skills in complementary disciplines. You will work jointly
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foundational computer science and mathematical foundations of AI; and experts in the industrial utilisation of emerging AI technologies for various manufacturing and built environment inspection processes
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of handling the nonlinear, probabilistic operations that generative AI tasks demand, which traditional digital computing systems struggle to process. Open problems in neuromorphic photonic reservoir computing
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An exciting opportunity has arisen for a brain stimulation Research Associate within the School of Medicine, Academic Unit, Mental Health and Clinical Neurosciences. As part of an MRC programme
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and machine learning, uncertainty quantification, Bayesian non-parametrics, image analysis, geometric statistics, and stochastic processes with an internationally leading research group in epidemic
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unique opportunity to be an integral part of a dynamic, multifaceted research programme, with reciprocal interdisciplinary engagement between themes (Genomics, Metabolomics, Advanced Medical Imaging
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will also conduct systematic reviews, organise and support expert advisory groups, and work with digital mental health technology partners Blum Health (https://blumtechgroup.com ) to design a prototype
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the School of Health Sciences, University of Nottingham. The HELM team comprises academics and learning technologists and have an international reputation for e-learning development and research in healthcare