131 machine-learning-"https:"-"https:"-"https:"-"https:"-"UCL" Postdoctoral positions in United Kingdom
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) in Physics or a related field. Previous experience in cosmological simulations, analysis of cosmic microwave background and/or large-scale structure datasets, machine learning methods applied
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thrusts within the lab’s multi-agent security programme. You should possess a completed PhD/DPhil (or thesis submitted by the start date) in Computer Science, Machine Learning, AI, Security, Robotics
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interaction to join a research group focused on studying learning and decision-making in humans and machine learning systems led by Prof Christopher Summerfield. The post-holder will have responsibility
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proud to be a signatory of the Armed Forces Covenant . an accredited Disability Confident Leader ; autism friendly university , committed to building disability confidence and supporting disabled staff
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students in the group. Candidates should have strong training in cross-disciplinary applied mathematics, with a demonstrated interest in biology, and experience in machine learning approaches is a plus. We
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of doctoral students in the group. Candidates should have strong training in cross-disciplinary applied mathematics, with a demonstrated interest in biology, and experience in machine learning approaches is a
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An exciting opportunity has arisen for a Postdoctoral Research Assistant in the Department of Physics. Machine learning has made enormous progress during recent years, entering almost all spheres
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for early-stage cancer using statistics and/or machine learning (including deep learning where appropriate). You will join a vibrant and growing research group of 12 scientists (six postdoctoral researchers
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turbines represented using an actuator-line approach, assess the applicability and limitations of reduced-order models in predicting turbine performance, and develop machine-learning surrogate models capable
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Computer Science, Chemistry, Chemical Engineering, Physics, or Materials Science. You will develop optimisation and machine-learning algorithms for human- and literature-informed discovery of new materials