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rigorous, collaborative research aligned with project goals. Develop and apply deep learning models, particularly in computer vision, NLP, and multimodal systems. Publish in peer-reviewed journals and
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climate scientists and artificial intelligence experts to generate new projections of the land ice contribution to sea level rise until 2300 with machine learning. You will develop probabilistic machine
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of the land ice contribution to sea level rise until 2300 with machine learning. You will develop probabilistic machine learning “emulators” of multiple ice sheet and glacier models, based on large ensembles
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on understanding the spread and control of human infectious diseases using modelling and pathogen genomics. This is a short-term opportunity to apply machine learning methods to two key projects. First, you will
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energy densities exceeding LMFP and competitive with NMC. A postdoctoral research position is available on this 3D-CAT project in the area of computer modelling and materials design of lithium battery
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Oxford’s Department of Orthopaedics (NDORMS) as well as collaborators in Bristol and Cardiff. You should have a PhD/DPhil (or be near completion) in robotics, computer vision, machine learning or a closely
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analysed by bespoke machine-learning driven algorithms, combined with physical models, to de-noise images, identify features and correlate properties, giving critical insights into power loss pathways
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reactions. We welcome applicants from diverse backgrounds, including computational chemistry, bioinformatics, systems biology, and machine learning. The project offers a unique opportunity to collaborate
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About the Role We are seeking an enthusiastic and motivated postdoctoral researcher to apply advanced data analytics and machine learning techniques to real-world clinical data in the field of viral
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The University of Oxford is seeking a highly motivated Postdoctoral Scientist with expertise in biostatistics, machine learning, and cardiac magnetic resonance imaging (MRI) to join Professor Betty