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activities as required. A PhD in statistics, machine learning, mathematical modelling or other relevant quantitative subject. Experience in infectious disease mathematical modelling. Experience with
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well as their documentation. Proven experience in the development of image processing and computer vision methods such as visual descriptors, motion descriptors, activity recognition and/or machine learning. Proven experience
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of machine learning techniques to build predictive models for outcomes such as joint replacement; Mendelian Randomisation studies utilising genetic data in UK biobank and other cohorts to establish whether
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of energy-efficient hardware, embedded machine learning and sensor-integrated nodes for the edge of the network. We offer a supportive and inclusive academic environment, with access to state-of-the-art lab
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that is pioneering transformative edge computing solutions including novel semiconductor devices, design and implementation of energy-efficient hardware, embedded machine learning and sensor-integrated
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multidisciplinary, combining domain knowledge with cutting-edge research to inform and develop the technologies and approaches that industry need to create the next generation of machines, products and production
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excellent experience of simulation methods, data analysis and advanced computing, and the opportunity to work with high performance computing and machine learning. Contract type: Open ended with fixed funding