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that are not seen in any other material. This project combines cutting-edge sampling techniques with machine-learned potentials for accurate phase predictions, offering considerable opportunity for method
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textiles, materials, soft robotics, sports, healthcare, machine learning and AI, with globally leading industrial and academic partners. Your Project The project focusses on the healthcare and sports
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Join our diverse and inclusive team to transform the future of aviation as part of the UK’s EPSRC Centre for Doctoral Training in Net Zero Aviation. Offering fully funded, multidisciplinary PhD
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in computer vision would be beneficial but not essential; determination, curiosity, and a willingness to learn are key attributes we value. Applicants with alternative qualifications, industry
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calculations of well-characterized 2D materials, simulations of electron microscopy images, and machine learning methods to reconstruct the 3D atomic positions of materials from a 2D microscopy image. The
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responsibility for the design and development of teaching and learning material and the delivery these across a range of modules within Early Modern History, including the third-year Special Subject ‘A New
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Overview Nature offers a mechanism - called homeostasis - by which life forms can maintain their physical integrity and well being. On the other hand, a series of machines, including robots, cannot
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cerium-rich alloys to delocalise and join the valence electrons triggering a dramatic change in properties. The project will explore building machine learning interatomic potentials for further modelling
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predict and rationalise XFEL observables are desperately needed such that XFEL results can reach their full potential. Aim This research aims to utilise the latest advances of computational methods (machine
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, these systems serve as complex functional approximators trained over an input-output data set. ‘Second Wave AI’ is the term used to describe the current glut of 'machine learning' style intelligence, where