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to lead projects aimed at developing a full-stack approach to suppressing errors in quantum hardware. This research focuses on achieving practical quantum computation by integrating techniques ranging from
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About the role We are seeking a full-time Postdoctoral Research Assistant to join the Hypersonics research group at the Department of Engineering Science, Osney. The post is fixed for 19 months with potential further extension, subject to confirmed funding. You will lead experiments in the OPG...
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citizens and businesses to re-imagine our transport systems. The programme will build an increasingly ambitious suite of real-world trials with communities, transport providers and government partners
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Mobility Reading Group led by Nobuko Yoshida. The successful candidate will be located in the Department of Computer Science Reporting to Professor Nobuko Yoshida, the post holder will be responsible
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hepatitis and liver disease. This post is funded by the National Institute for Health and Care Research (NIHR) as part of a significant research programme that leverages large-scale healthcare datasets
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United Kingdom Application Deadline 7 Sep 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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research project based in the groups of Prof. Aurora J. Cruz-Cabeza and Prof. John Evans. The project is part of a new £7m EPSRC funded Programme Grant that brings together a team of researchers from
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Location: Old Road Campus Research Building, Headington, Oxford, OX3 7DQ We are seeking five full-time Postdoctoral Research Assistants to join the Computational Health Informatics Lab
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We are seeking five full-time Postdoctoral Research Assistants to join the Computational Health Informatics Lab at the Department of Engineering Science, based at the Institute of Biomedical
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models