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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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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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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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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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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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foundational understanding of children's agency in digital environments increasingly dominated by AI systems. The UCL team is specifically focusing on the educational technology angle, developing agency
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research in fundamental & applied AI that is directly relevant to policy. to develop and deliver expert-led training on AI to civil servants across government. Fellows will spend 50% of their time on each