38 bayesian-inference-tracking Postdoctoral positions at University of Oxford in United Kingdom
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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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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly
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inference attacks, to mitigate privacy leaks in MMFM. You will hold a PhD/DPhil (or be near completion) in a relevant discipline such as computer science, data science, statistics or mathematics; expertise in
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available data and apply causal inference methods, including Mendelian randomisation, to identify candidate mechanisms linking circadian misalignment and sleep disturbances with cardiometabolic disease
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. Armed with this information, the post holder will use cutting-edge paleoclimatic modelling that incorporates nutrient cycling and carbon chemistry (HadOCC) to infer the distribution of potential feeding
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a track record of peer-reviewed publications are essential. This 24 month position is available from January 2026. Group website with research details and publications: https://emi.web.ox.ac.uk All
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applicant should hold or be near the completion of doctoral studies into hypersonic flows or numerical methods or hold equivalent professional experience. The ideal applicant should have a clear track record
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, microscopy, flow cytometry and quantitative real-time PCR. You will have a strong track record of writing papers as evidenced by publications or submitted manuscripts in scientific journals, and have evidence
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suited to a Postdoctoral Researcher who has established expertise and track record in cardiovascular disease, and could benefit from support of the BHF’s award to develop their career and make major
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related field. You have an excellent academic track record in topics relevant to robot perception - visual inertial odometry (VIO), mapping (SLAM) and 3D reconstruction. Experience with ultra-sound would be