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Field
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of causal reasoning tools, including causal inference, counterfactual analysis, causal discovery. Development of deep learning methods on computer vision. Job Requirements: Preferably PhD in Computer
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This role will be based on the university campus, with scope for it to be undertaken in a hybrid manner. We are also open to discussing flexible working arrangements. Are you a Computer Scientist
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(PhD) (completed or near completion) in Human-Computer Interaction (HCI), Communication, Computer Science, Information Science, Psychology, or a related field. Proven track record with publications in
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. Are you a Computer Scientist looking to apply your expertise to real-world weather forecasting challenges in Africa? Machine-learning has the potential to revolutionise weather prediction for and in Africa
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advanced statistical methods. Experience working in a multi-disciplinary setting and/or teams. Experience with Microsoft Suite products and working knowledge of at least one statistical software (E.g. SAS
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, Laboratory for solid-state synthesis and catalysis, to work experimentally on solid-state synthesis and monitoring of the reactions using spectroscopic methods, for a fixed term of 24 months, 1 position
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-disciplinary team of researchers, including bioinformaticians, pathologists, oncologists, and computer scientists, and conduct original research on computational pathology. Digital pathology images contain rich
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Solar Radiation Management (SRM) methods to artificially cool the Earth by reflecting more sunlight back into space, buying time for global decarbonisation. The main SRM methods are: 1) Stratosphere
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for constructing correctness proofs, yet the standard symbolic methods face significant limitations in both expressivity and scalability. This project proposes novel techniques for constructing formal proofs
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(STFC, Daresbury), Prof. Jonathan Tennyson (University College London) and Prof Michael Charlton (Swansea). The Research Fellow will work on the development of methods and computer programs adapted