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Field
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will use large genomics databases such as the UK Biobank, a collection of 500,000 individuals including genetic and healthcare records. The project is a data analysis project – from day to day you will
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. You will focus on machine learning, but will be involved in all areas. There are also spinout opportunities. For details: PhD information sheet The team have wide experience studying bumblebee behaviour
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technology (FinTech) Payment technologies and the future of money Explainable artificial intelligence (AI) in financial services Integration of FinTech and big data in financial markets and sustainable finance
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of insect pollinators from large-scale photographic and video datasets. The research will integrate ecological fieldwork, computer vision and stakeholder engagement to: 1.Develop and optimise deep learning
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correction. This machine-learning approach, however, needs a realistic model of light propagation in the retina in order to validate it and to generate the large volumes of training data required. Funding
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thermodynamically. Performance design optimization and advanced performance simulation methods will be investigated, and corresponding computer software will be developed. The research will contribute
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approaches to interpreting these large datasets, as well as computational models that capture low-dimensional structure that reflects the architecture of the neocortex. By working with researchers developing
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Can We Teach AI to Outsmart Humans in the Werewolf Game—Without Changing the AI Itself? Large Language Models (LLMs) have dazzled us with their ability to converse, code, and create—but they still
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delivered in routine practice for people with alcohol and drug dependence. This will be a large-scale longitudinal cohort study using national registry data on employment and health. A target trial emulation
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rapid economic and social change. Controlled cross-cultural studies will be informed by locally-led participatory research. Two large scale trials are underway/in preparation in Colombia and Nicaragua