29 assistant-professor-computer-science-and-data-"Meta" Fellowship positions at University of London
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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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science methods, ideally to environmental health data, and conducting systematic reviews and meta-analysis. Further particulars are included in the job description. The post is full-time 35 hours per week
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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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exciting project that will develop new approaches to handle missing data in statistical analyses based on machine learning methods. The Research Fellow will be based in the Department of Medical Statistics
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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