30 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" research jobs at University of Southern Denmark
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strategy (PMIDs: 29123070, 33621493, 33087936, 30566856, 39947938; doi: https://doi.org/10.1101/2025.03.15.641049 ). Postdoctoral Projects Project 1: Replisome Dynamics, Replication Stress, and Cancer
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opportunities to explore the intersections between these disciplines. Reda more here: https://www.sdu.dk/en/om-sdu/institutter-centre/fysik_kemi_og_farmaci/ominstituttet Job Info Job Identification 3512 Job
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more about the CAPeX research themes and X-trails, our organization, and the other open PhD and postdoc cohort positions at http://www.capex-p2x.com . We look forward to receiving your application and to
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/InstituteNational Institute for Public HealthCountryDenmarkGeofield Contact City Odense Website http://www.sdu.dk Street Campusvej 55 Postal Code 5230 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp
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funded by the CAPeX Pioneer center (https://capex.dtu.dk/ ). The project involves design, synthesis, characterization, and testing of molecular transition metal coordination compounds, as electrocatalysts
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employ cutting-edge single-cell and spatial omics technologies with bioinformatics and machine learning to decipher principles of gene regulation underlying cell identity and its disruption in human
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initiatives, as well as a wide range of research-related tasks such as qualitative data collection and analysis as well as writing academic publications. More information on “Digging for the Climate”: https
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particular emphasis on preparing analysis-ready datasets that support downstream statistical and machine learning workflows. What you would be doing You will contribute to data access workflows, database and
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Job Description The Centre for Machine Learning within the Data Science and Statistics Section of the Department of Mathematics and Computer Science (IMADA) at the University of Southern Denmark
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relevant field. In-depth knowledge and experience with advanced data processing and statistical analysis in R; knowledge and experience in spatial modelling, machine learning, or computational methods