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the next generation of PV technologies for beyond 2030. The new postdoctoral research position will use materials modelling techniques (DFT, molecular dynamics, machine learning potentials) to investigate
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have: Experience with AI and machine learning for medical images Experience working with data from multiple hospitals An interest in rare disease research. Additional information Informal enquiries
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mathematics or a related field. The successful candidate will have expertise in at least in one of: Machine learning in the context of physical systems AI-based condition monitoring Reinforcement learning
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We are seeking a highly talented and experienced Postdoctoral Researcher to join a research team led by Prof Chris Summerfield focussed on studying learning and decision-making in humans and machine
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are passionate about applying machine learning to real-world clinical challenges. The successful candidate will lead the development and validation of predictive models using multimodal data including neuroimaging
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are passionate about applying machine learning to real-world clinical challenges. The successful candidate will lead the development and validation of predictive models using multimodal data including neuroimaging
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for Computer Animation, The Media School and the School of Psychology. The breadth of subject areas in the Faculty means our cutting-edge research is delivering real benefits to digital creative industries
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Location: Kavli Institute for Nanoscience Discovery Contract type: 1 year Fixed-term (with the possibility of an extension) We are seeking a Postdoctoral Research Assistant for the Gene Machines
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We are seeking a Postdoctoral Research Assistant for the Gene Machines’ group, led by Prof Achilles Kapanidis. The group is well known for developing single-molecule and single-cell fluorescence
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they are kept fully up to date with progress and difficulties in the research projects. It is essential that you hold a PhD/DPhil in a quantitative discipline (e.g. Statistics, Machine Learning, Biostatistics, AI