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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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We are seeking a full-time Postdoctoral Research Assistant to join a cross disciplinary research project to improve our understanding of colorectal cancer. Deep learning has revolutionised image
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journal publications dependent on your background discipline(s) and should hold sufficient theoretical knowledge of deep learning-based methodologies as well as working with real-world data. Informal
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are comfortable navigating complex HPC environments and wrangling large datasets. You have experience with modelling through state-of-the-art machine and deep-learning methods and with hands
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knowledge of methodologies such as deep and statistical learning. Informal enquiries may be addressed to Prof. Andrea Vedaldi (email:andrea.vedaldi@eng.ox.ac.uk) For more information about working at
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require a deep understanding of the classical infrastructure that supports them, including analog control systems. As quantum devices scale toward the million-qubit regime, modeling these complex systems
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cryoEM and cryoET you will ideally have background in at least one of these methods. You also should have a deep interest in mechanisms underlying basic biological processes at the molecular level
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approach is a deep commitment to the training and career development of our staff and students Applications for this vacancy are to be made online and you will be required to upload a supporting statement
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should be an expert in at least one of those techniques and keen to learn the others. You also should have a deep interest in molecular mechanisms underlying biological processes and – if not experience
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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