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machine learning algorithms and to assess when AI predictions are likely to be correct and when, for example, first principles quantum chemical calculations might be helpful. Predicting chemical reactivity
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machine learning algorithms and to assess when AI predictions are likely to be correct and when, for example, first principles quantum chemical calculations might be helpful. Predicting chemical reactivity
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The always-on, safety-critical nature of air traffic control raises rich and exciting challenges for machine learning and AI. The University of Exeter in partnership with NATS, the UK’s main air
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part of the larger project. The scope of the PhD project is to implement, use, and where required develop, statistical machine learning tools to identify DNA mutations that cause particular types
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PhD Studentship: Accelerating Statistical Algorithms through Machine Learning Award Summary 100% home fees covered, and a minimum tax-free annual living allowance of £19,237 (2024/25 UKRI rate
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; Midlands Graduate School Doctoral Training Partnership | Nottingham, England | United Kingdom | 2 months ago
ESRC DTP Strategic Joint Studentship University of Nottingham and University of Birmingham The Midlands Graduate School is an accredited Economic and Social Research Council (ESRC) Doctoral Training Partnership (DTP). One of 15 such partnerships in the UK, the Midlands Graduate School is a...
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is to develop a highly innovative ‘Lab on a Bench (LoB)’ setup, integrated with Machine Learning algorithm, as a high throughput method for screening and developing formulated products that are used in
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Supervisors: Prof. Gabriele Sosso, Dr Lukasz Figiel, Prof. James Kermode Project Partner: AWE-NST This project utilises advancing machine learning techniques for simulating gas transport in
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optimization of batteries against the swelling phenomenon. This project aims at developing scientific machine learning approaches based on the Bayesian paradigm and electrochemical-thermomechanical models in
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Project title: Privacy/Security Risks in Machine/Federated Learning systems Supervisory Team: Dr Han Wu Project description: In the wake of growing data privacy concerns and the enactment