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, Organometallic, Organic Chemistry and Machine Learning for a period of up to 36 months. The project, funded by EPSRC, will involve exploring the use of machine learning to develop new tools for investigating
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Background This role is central to developing a point-of-care blood test device for pre-hospital diagnostics. Based in the Department of Chemical Engineering at the University of Manchester, you
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CoRE) in Exposome Immunology, to be hosted jointly by the universities of Manchester and Oxford. The CoRE will leverage cutting edge computational approaches, novel experimental models, and experimental
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Applicants are invited for the above vacancy in the Division of Informatics, Imaging and Data Sciences, University of Manchester. You will join the Division and take responsibility for an area of
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development of a computational pipeline that integrates multi-omic data at the cellular level across exposomes and diseases, revealing novel biology and shared mechanisms of immune regulation. You will be
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widening participation schemes to enable junior researchers to gain experience in the lab. The candidate will have: A qualification at QCF level 6 (such as a bachelor’s degree) in a relevant biological science
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of progress. We helped usher in the computer age in 1948 with the world’s first stored-program computer “The Baby” and Alan Turing helped shape what would become the foundations of AI right here on campus. Home
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engage and influence stakeholders across diverse disciplines. Not essential but desirable: Higher degree in AI, computer science, or related field (or equivalent experience). Familiarity with higher
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in combination with X-ray crystallography, enzyme kinetics and computational chemistry to investigate how enzymes utilise changes in conformational entropy to control the relative stability
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materials • AI, data and advanced computing We seek to employ an Application Scientist with expertise in the materials science of one of the following: sustainable polymers, nanomaterials, data analytics