31 assistant-and-professor-and-computer-and-science-and-data-"U" Fellowship positions at University of London in United Kingdom
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for a Research Fellow in Bioinformatics/Computational Biology to help develop, coordinate, and conduct robust analysis of high-throughput host protein data under supervision using advanced analytical and
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. The post-holder must have a postgraduate degree, ideally a doctoral degree (for Research Fellow) or a doctoral degree (for Assistant Professor) in epidemiology, medical statistics or health data science
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Assistant Professor) to support primarily two new UKRI projects with additional ad hoc statistical analysis and epidemiological interpretation for projects in the thriving laboratories of Professor Chris
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environment. Further information on the programme is available at: PROGRAMME | CREATE PhD Programme (create-phd.org) This programme is aimed at supporting health professionals who wish to undertake rigorous
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in partnership to achieve excellence in public and global health research, education and translation of knowledge into policy and practice. We are seeking to appoint a Research Assistant or Research
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in partnership to achieve excellence in public and global health research, education and translation of knowledge into policy and practice. The Baby Ubuntu programme is a group-participatory programme
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access to cutting-edge technology across the UK healthcare and biotech sectors. Read more about the initiative here This is a unique opportunity to help build a first-of-its-kind cancer AI development
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to work in Professor Polly Roy’s dynamic and productive research laboratory at LSHTM. The post is funded by Wellcome Trust and is focused on double-stranded RNA virus replication. Applicants should be
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, Professors Ruth Keogh and Kate Walker. Applicants should have a postgraduate degree, ideally a PhD, in medical statistics, epidemiology, health economics or a related field. Relevant experience in applying
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, relevant experience in computer-based statistical analysis and presentation of results, demonstrated proficiency in a coding language used for data analysis, such as Python or R, strong quantitative skills