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the accurate prediction of reaction enthalpies and activation free energies for all relevant intermediates. In this project, a deep learning and generative design toolchain will be developed resulting in an ML
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powerful framework for decentralised machine learning. FL enables multiple entities to collaboratively train a global machine learning model without sharing their private data, thus enhancing privacy
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materials are connected is critical for the development of next generation functional materials. However, modern atomically-resolved imaging techniques only give an integrated snapshot of the structure
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, and digital approaches using mutual learning, inclusive theory-development and creative methodologies (e.g. filmmaking, VR technologies) The successful candidate will support the Co-Investigator in co
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University Technology Centre (UTC) in Manufacturing Technology and On-Wing Technology (https://www.nottingham.ac.uk/utc/index.aspx ) at the University of Nottingham. Having state-of-the-art purpose-built
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safety? If so, this PhD opportunity is for you. The safe long-term storage of irradiated stainless steel fuel cladding is a major challenge in nuclear energy. This project will develop a novel, physics
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A PhD opportunity at the EPSRC Centre for Doctoral Training in Quantum Information Science and Technologies at the University of Sussex School of Mathematical & Physical Sciences The University
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: The completed AHRC NWCDTP Application Form and Equality and Diversity Monitoring Form must be submitted to the Humanities Doctoral Academy via hums.doctoralacademy.admissions@manchester.ac.uk no later than
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-quality videos to guide the restoration and enhancement of distorted videos. Our goal is to develop a comprehensive framework for video restoration by tackling blind inverse problems with unsupervised
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. This project will develop and apply new computational/analytical tools to guide XFEL experiments for specifically tracking lattice fluctuations and ion dynamics in energy materials (batteries). The project will