DTU Studieprojekt – Decoding metabolic disease using single-cell technologies genomics and data science – Danmarks Tekniske Universitet (DTU) – Copenhagen

Decoding metabolic disease using single-cell technologies genomics and data science Udbyder Virksomhed / Organisation Sted København og omegn Exciting project in translational neuroscience using single-cell technologies, large-scale genomics and data science to understand the role of the brain in obesity and type 2 diabetes.In the Pers lab at the Novo Nordisk Foundation for Basic Metabolic Research (CBMR), we have established molecular techniques for massively parallel profiling of single-cells and are now leveraging these techniques – by generating data and developing computational tools – to better understand the brain’s role in metabolic health and disease. Our group comprises about 12 members, from more than five countries and from various disciplines. We are part of an interdisciplinary environment spanning in vivo physiology, transgenic animal models, human genetics and computational biology and closely collaborate with stem cell groups (reNEW), we are part of the Novo Nordisk Foundation Center for Genomic Mechanisms of Disease at the Broad Institute (USA), and we closely collaborate with world-leading neuroendocrinology labs.Websitehttps://cbmr.ku.dk/For more information contactTune H. Pers, tune.pers@sund.ku.dk, Associate Professor, or Cecilia E. Thomas, cecilia.thomas@sund.ku.dk, PhD.RequirementsWe are looking for master’s students and talented bachelor students with an interest in data science and understanding brain biology. You should have a background in computational biology, statistics, data science and/or molecular biology, and have substantial experience in R and/or Python programming.The projectWe are offering projects spanning 6-12 months and are looking for motivated and engaged students who would like to apply state-of-the-art data science techniques to large-scale transcriptomics and epigenomics data generated from human postmortem brains. Specifically, the student project will be centered around integrating single-cell transcriptomics and epigenomics data with large-scale genomics data to build and test risk prediction models for obesity and type 2 diabetes. Emneord Gener og genomerDataanalyseStatistikSundhed og sygdomme Kontakt Virksomhed/organisationUniversity of CopenhagenNavnCecilia ThomasStillingPost docMailcecilia.thomas@sund.ku.dk Forslag til Uddannelsesretning Kandidatuddannelsen i BioteknologiKandidatuddannelsen i Bioinformatik og SystembiologiBachelor i BioteknologiBachelor i Teknisk BiomedicinKandidatuddannelsen i Matematisk Modellering og ComputingDiplomingeniør, SundhedsteknologiBachelor i Matematik og TeknologiKandidatuddannelsen i Anvendt KemiKandidatuddannelsen i FarmateknologiKandidatuddannelsen i Kemisk og Biokemisk TeknologiKandidatuddannelsen i Medicin og TeknologiDiplomingeniør, Fødevaresikkerhed og -kvalitet (tidl. Fødevareanalyse)Bachelor i Medicin og Teknologi

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