65 algorithm-"Multiple"-"U"-"Simons-Foundation" "Prof" uni jobs at University of Manchester
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deep learning and generative AI approaches, creating synthetic virtual patient cohorts from multimodal datasets. Your work will involve designing advanced algorithms and high-throughput workflows
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this role, you will work as part of the world-class team of researchers and software developers within the PSS team to develop all or some of firmware, software and algorithms for pulsar and fast transient
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will play a major role in supporting the administration within the portfolio, working closely with Prof Frangi and the Programme Manager and will involve working proactively with multiple teams in
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Gittins, Prof. Martie van Tongeren and Prof. Andy Povey. The successful candidate will be required to support a cross-institution, multi-disciplinary research team to successfully deliver the programme
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the sustainability of engineering plastics, with a focus on applying fundamental polymer science to industrially relevant projects. As we are recruiting for multiple roles, expertise in mechanical recycling, chemical
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and gut microbiome, funded by an 8-year Wellcome CDA in collaboration with Prof. Matthew Hepworth. During this position, the post-holder will design and lead bioinformatic analyses of large-scale
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researchers, under the supervision of Prof David Wedge. Collectively, this team has expertise in the analysis of multilevel omic and imaging data; data integration and machine learning; risk prediction. This
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to enquiries, accept CVs or applications from Recruitment Agencies. Any CV’s submitted by a recruitment agency will be considered a gift. Enquiries about the vacancy, shortlisting and interviews: Name: Prof Andy
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Applications are sought for a full-time Postdoctoral Research Associate to work with Prof Edmond Smith, conducting research for the ERC-selected, UKRI-funded project “Institutional Transformation
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, and use smart phone apps to collect passive and active data using a prospective observational cohort study design. We will use this data to develop and validate a personalised risk prediction algorithm