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and service activities in line with the School/College’s strategic objectives and as appropriate for the job role. This is a Post-doctoral role in Marine and Freshwater Biology at the School
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and most comprehensive dataset on multiple sclerosis (MS), encompassing longitudinal data from over 40,000 individuals, some tracked for more than a decade. You will be responsible for advancing and
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individuals, some tracked for more than a decade. You will be responsible for advancing and applying state-of-the-art probabilistic deep generative models, including conditional diffusion and flow matching
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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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) Experience in the use of neuroimaging analysis (fMRI, MRI) to study mechanisms of brain function Previous experience of using Bayesian methods in both model development and fitting. Previous experience and
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), and sustainable chemistry. In particular, the role will involve: (i) designing blockchain architectures and smart contracts for CO2 credit tracking, tokenisation of CO2 derived products; (ii
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at the intersection of blockchain, artificial intelligence (AI), and sustainable chemistry. In particular, the role will involve: (i) designing blockchain architectures and smart contracts for CO2 credit tracking
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within medical imaging and computational modelling technologies. Our objective is to facilitate research and teaching guided by clinical questions and is aimed at novelty, understanding of physiology and
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systems onto real robots for tasks such as tracking, 3D reconstruction, object recognition, and visual SLAM. They will be working with a team composed of PhD students, Research Assistants, and Postdocs
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techniques from statistical physics, Bayesian inference, and complex systems theory to address challenges posed by noisy and incomplete data. Depending on the results obtained in the first year, the post can