4,036 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions in United Kingdom
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high 2:1 in computer science, mechanical engineering, or aerospace engineering. You should have programming experience applied to physics/engineering problems and/or experience with machine learning and
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, researchers and practitioners to enable dual learning and original contributions to both research and practice. We wish to appoint a Policy Engagement Manager and the purpose of the role is threefold
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experience of carrying out grounds maintenance tasks, preferable in a commercial setting • Previous experience of the safe use of common grounds maintenance tools and machines • A willingness to learn and
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establish a digital route to quantify the segregation behaviour of residual elements at austenite/austenite grain boundaries through atomic-scale simulations, using modern machine learning techniques and in
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sensors - if we can control and tune their properties. You will develop and use top-of-the-line machine learning models to predict the sensor response of these materials under realistic conditions
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OF RESPONSIBILITY Understand the problems of the Turing’s partners and develop appropriate approaches. Perform experiments and develop capabilities, which might include: building and deploying machine learning models
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experience in cosmological simulations, analysis of cosmic microwave background and/or large-scale structure datasets, machine learning methods applied to cosmology, or theoretical modelling of cosmological
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the Centre, enables collaborations in data analysis, computational modelling, machine learning and theory. SWC also benefits from interaction with the wider UCL Neuroscience community, which brings together
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a lead in advising and delivering on space planning initiatives and project development across our student’s teaching and learning spaces and in places of work for our staff. Undertaking spot space
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. Current XAI methods are often generic and overlook industrial realities. This project will embed user-centric explanations directly into machine learning workflows using structured, ontology-driven