7 science "https:" "https:" "https:" "https:" Postdoctoral positions at University of Manchester
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, Organometallic, Organic Chemistry and Machine Learning for a period of up to 24 months. The project, funded by EPSRC, will involve exploring the use of machine learning to develop new tools for investigating
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building practical technology demonstrations of the fabricated silicon. This position is embedded within a long-standing research programme on vision sensors and neuromorphic computing circuits in
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aspects of these new architectures. Additionally, the role involves interfacing with high-speed sensors and building practical technology demonstrations. This position is embedded within a long-standing
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fusion science & technology, in the Tritium Science and Technology (TST) research group at the University of Manchester. The TST group conducts research focused on tritium behaviour in materials, tritium
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this, the postdoctoral researcher will combine machine learning, molecular dynamics simulations and high performance computing (Isambard AI). Applicants must have a PhD in an appropriate area of computational chemistry or
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within a dynamic and inclusive environment, in the Hepworth lab in the areas of Mucosal Immunology, ILC biology and relevant interdisciplinary fields (e.g. neuroimmunology, matrix biology, metabolism, etc
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within a dynamic and inclusive environment, in the Hepworth lab in the areas of Mucosal Immunology, fibroblast and matrix biology. This would be expected to include independently performing experiments