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predicts battery performance and properties from fabrication line measurements. About you Hold (or be near completion of) a PhD/DPhil in Control Engineering or a related subject, with the possibility
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and PhD students) and openly share expertise knowledge with team members (e.g. Post-docs). Collaborate with other two post-docs working in this research programme, to deliver on project aims. Contribute
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Application Deadline 23 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 related to staff
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, education and wider student experience, but also on our keen sense of community and of inspiring others to achieve their potential. Our Purpose and Values We want our University to be a place where people can
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: PhD or equivalent degree in Robotics, Computer Science, Machine Learning, AI, Control Engineering, or a related field. Excellent programming skills and experience with related tools and software. A
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to artificial intelligence (AI) (e.g. computer science, engineering, Statistics, and mathematics etc.) The post is available for 30 months, starting on 1 September 2025. If you are still awaiting your PhD to be
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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
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posters locally and at national and international conferences, as well as participate in MRC grant’s research programme led by Prof Marco Fritzsche. You must hold a relevant PhD/DPhil (or be near completion
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at conferences and seminars. The successful candidate will be required to work in collaboration with other postdocs and PhD students in the lab. As such, the ability to work in a team is essential. This role will
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of the research team, visiting scientist and international collaborators. Members of the department are also encouraged to take part in postgraduate teaching (mostly MSC students) that would typically amount