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other researchers of the Learning domain and C-LaBL at large. Contact For further information about the position, please contact Professor Øystein A. Vangsnes: email: oystein.vangsnes@uit.no or Professor
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information on the CRC’s research and its projects can be found at https://www.sfb1372.de/ The CRC hosts a state-of-the-art research infrastructure including a large interdisciplinary network of researchers
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range of studies and the methodologies to be used. The post will offer opportunities to apply a variety of data sciences approaches and work with a wide range of large health/clinical/biological datasets
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proposals. Have a PhD in biostatistics or related subject with a numerate or computational component (including machine learning, data science, mathematics or a computational science), or a postgraduate
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: Erlangen Programme for AI” This is a 5-year programme supported by the EPSRC and is a collaboration of mathematicians and computer scientists at the University of Southampton, the University of Oxford (lead
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potential research topics to improve the project results. Research topics may include interventions in public services, labor markets, marketing, and digital platforms, using large-scale data and algorithmic
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, metabolomic and metagenomics data Large-scale clinical and molecular phenotypes data, including integrative omics studies Evaluation and application of appropriate bioinformatics/statistical techniques, as
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Faculty of Life Sciences and Medicine Hub for Applied Bioinformatics). We are looking for an ambitious candidate with established expertise in bioinformatics, specifically dealing with large data sets and
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: Experience with numerical modeling and/or data analytics with big data. Broad knowledge of hydrology. Experience in ML applications. Background Investigation Statement: Prior to hiring, the final candidate(s
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for handling data collection, surveys, publications, and logistics for the mCDR project 3 year fixed term, part-time (0.8 FTE) position based in Hobart About the opportunity The Research Fellow will contribute