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50 Faculty of Life Sciences Startdate: 01.08.2025 | Working hours: 40 | Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 31.07.2029 Reference no.: 4160 Explore and teach
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analysis of PDEs (with deterministic and/or stochastic methods), Gaussian Random Fields, mathematical foundations of deep learning, functional analysis and measure theory. You can find more information about
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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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responsibility for implementing a deep learning work-package as part of a Cancer Research UK-funded programme, developing an image-recognition model to identify morphological features corresponding to clonal
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for deep access within the human body. The research remit will encompass: mechanical and electronic circuit design, prototyping, and pre-clinical evaluation of diagnostic and therapeutic devices to tackle
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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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precisely monitor changes in the global distribution of CO₂ sources and sinks. The UK science lead for MicroCarb is at the University of Edinburgh so this opportunity is a valuable opportunity to gain a deep
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interactions that lead to immunothrombosis in deep vein thrombosis. This work builds upon seminal work from the research group based at City St George’s University of London and Imperial College that identified
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of turbidity currents in action in the deep-sea, and to develop novel technologies for monitoring these seabed sediment flows. Turbidity currents form the deepest canyons, longest channels and largest sediment
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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