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We are seeking to appoint a Senior Postdoctoral Researcher in Statistical Machine Learning and Deep Generative Modelling to apply and develop cutting-edge deep generative probabilistic models
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out rigorous and impactful research into the computational mechanisms of human learning using deep neural network models, and disseminating the findings within the research group, across the wider
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-genome deep-sequencing data collected as part of the Office for National Statistics Covid Infection Survey, with a focus on using household data to enable methods for determining who-infected-whom using
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hold, or are close to completing, a PhD in robotics, robot learning, or a closely related field. You possess strong expertise in deep learning and robot navigation, with hands-on experience in deploying
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methodology, theory, and applications across the areas of Bayesian experimental design, active learning, probabilistic deep learning, and related topics. The £1.23M project is funded by the UKRI Horizon
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institutions. You will lead the computational aspects of this exciting project by leveraging AI tools such as AlphaFold and developing novel deep generative models and/or large language models. The aim is to
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electronic health records (EHRs) from multiple UK hospital centres using advanced data analytics including machine learning, deep learning, and statistical techniques—with a particular emphasis on deep
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rules which enable effective learning in large and deep networks and is consistent with biological data on learning in the cortex. In particular, the research will focus on evaluating and extending a
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project will likely use a combination of single particle cryoEM, cryoET, and X-ray crystallography, you should be an expert in at least one of those techniques and keen to learn the others. You also should