264 parallel-and-distributed-computing-phd-"Meta"-"Meta" positions at University of Manchester
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atlases along with computational models to characterise the effect of exposures on different tissues in humans and model systems. You will have a PhD with a significant computational and/or statistical
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the centre. Successful applicants will have (or be about to obtain) a PhD in computational biology or computer science, with knowledge of multimodal spatial omics data integration and machine learning
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understanding of developmental biology. Candidates must have, or be about to obtain, a PhD in a relevant biological/mathematical discipline, including an understanding of algebraic topology. Please refer to
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/SIMULINK. The research is part of a project to investigate future network performance funded by National Grid Electricity Transmission through the Network Innovation Allowance. You should have a PhD or
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on the online programme application and supporting documents. Application form Additional documentation Your full online application must include; A 1,500 word PhD research proposal. Times New Roman, Font
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thereafter, for 1 year in the first instance, with the potential for renewal for a further year. The post is part of an EPSRC-funded research programme (PhotoOxyEdit), looking to develop photochemical methods
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of Manchester and Oxford. The CoRE will leverage cutting edge computational approaches, novel experimental models, and experimental medicine studies to uncover how pollutants and infections interact with our
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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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by the universities of Manchester and Oxford. The CoRE will leverage cutting edge computational approaches, novel experimental models, and experimental medicine studies to uncover how pollutants and
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. These studies will include detailed characterisation of molecular weight distributions, degree of crosslinking, thermal-mechanical modelling and microstructural features that influence electrical performance