24 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Dr"-"FEUP" PhD positions at University of Southern Denmark in Denmark
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Computer Science, fully funded by a major research project from the Novo Nordisk Foundation (NNF). The successful applicants would become part of the Data Science & Statistics section at the department
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across news outlets, social media platforms, and individual news diets, drawing on, among other data sources, data donations from individuals and automated content analyses. SP2 will examine how people
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of machine learning Distributed and federated training The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics
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portfolio of hypothesis-generating screening studies, a methodological portfolio where we identify signals of interest from large real-world register data to guide the conduct of further studies according
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single‑photon detector (SNSPD). Additional responsibilities include developing efficient coupling of free‑space optics to optical fibers, conducting extended data‑taking runs with TES and SNSPD systems
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research environment and supervisor team with expertise in pharmacoepidemiology, pediatrics and child and adolescent psychiatry. We combine clinical perspectives and data sources with advanced population
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registration number) – in this case, the CPR number must be crossed out. Applicants are encouraged to read the information "How to apply" before applying. If you experience technical problems when uploading
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central role in SDU’s ambition to be a national and European hub for semiconductor and chip innovation. Further information For further information about the position, please contact Professor Farshad
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Information Further information about this position is available via email from Professor Ahmad Rafsanjani (ahra@mmmi.sdu.dk ). If you experience technical problems, please contact our email support
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. You will also spend 3 months at Georgia Tech/Emory University (USA), working on machine learning and data benchmarking. Work description The selected PhD student will be responsible for the full