352 machine-learning "https:" "https:" "https:" "https:" "https:" "U.S" PhD scholarships in United Kingdom
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industry and academia together to drive pre-competitive, fundamental research in polymers. We welcome applicants with interests in polymer physics, materials processing and characterisation, machine learning
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gravitational effects on entangled photons for shining light onto the interface of quantum physics and gravity? Can we exploit quantum photonics technology for novel quantum machine learning, quantum computing
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biodiversity support, cooling, air quality regulation and access to nature. By integrating Earth observation, spatial AI, machine learning and socio-environmental datasets, the project will reveal where blue
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to think analytically and creatively. Good computer skills, plus good presentation and writing skills in English, are required. Previous research experience in contributing to a collaborative
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. Although individually both temperature extremes (e.g. heat-stress) and air quality (e.g. Nitrogen Oxide from car fumes) are known to severely impact human health, it is unclear how these stressors interact
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computer science, mechanical engineering, or aerospace engineering. You should have programming experience applied to physics/engineering problems and/or experience with machine learning and ML. The University
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this industrial PhD studentship in Physics – fully funded by the University of Exeter and Leonardo UK. We’re looking for a student who has a passion for science, with ambition to learn and apply their own ideas
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venues including Serpentine Arts Technologies, Southbank Centre, Barbican Immersive and more, you’ll develop cutting-edge research skills alongside practical expertise in machine learning, extended reality
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, Chemistry, Physics, Engineering, Mathematics, Computer Science, Data Science, Machine Learning or Artificial Intelligence a minimum 2:1 undergraduate degree (or equivalent) Excellent spoken and written
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, analyse learning from past incidents and exercises, and co-develop practical frameworks or tools to support improved cross-agency working. These will be tested through scenario-based evaluation and