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COG-MHEAR is a world-leading cross-disciplinary research programme funded under the EPSRC Transformative Healthcare Technologies 2050 Call. The programme aims to develop truly personalized
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highly motivated researcher to develop artificial intelligence based novel algorithms and computational workflows to predict the impact of mutations on genes in the avian flu virus and the viral host which
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perceptual and cognitive tasks, investigating the generality of behavioural biases. A recently-developed statistical sampling model of human cognition will then be compared against existing approaches with
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binding pockets. About the role We are seeking a highly motivated researcher to develop artificial intelligence based novel algorithms and computational workflows to identify domain functional families
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inversion techniques and signal processing. Strong programming skills, Proficiency in scientific computing (e.g. Python, MATLAB, or similar) for algorithm development and data handling. Experience with sensor
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Research Fellow in Intervention Development to join the Big Data in Health Group About us Our big data in health team at the University of Southampton is based in the Primary Care Research Centre
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developing and devising machine learning algorithms in an energy context Ability to assess research resource requirements, and use resources effectively, to plan and manage research activity Strong analytical
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HiPerBreedSim project. In this role, you will leverage recent advances in working with ancestral recombination graphs (ARGs) to develop algorithms and code for simulating population genomic data, including
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real-time, and will be tested and demonstrated on a state-of-the-art HiL rig and an autonomous test vehicle. The post is focused on the development of automotive-grade algorithms and estimators that will
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real-time, and will be tested and demonstrated on a state-of-the-art HiL rig and an autonomous test vehicle. The post is focused on the development of automotive-grade algorithms and estimators that will