499 data-"https:"-"https:"-"https:"-"https:"-"https:"-"IRIBHM-ULB" positions in Denmark
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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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Work The place of work is Ny Munkegade 120, 8000 Aarhus C. Contact Information Further information about the position may be obtained from / For further information please contact: Dr Simon Wall +45
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how geometry- and data-driven digital twins of wireless environments can support learning, inference, and coordination in physical AI systems such as robots, vehicles, or distributed sensing platforms
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. Starting date is 15 April 2026 (or according to mutual agreement). The position is a full-time position. You can read more about career paths at DTU here . Further information Further information may be
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register and survey data. The integration of migrants and questions of potential return migration are increasingly important social issues across Europe, including Denmark. As many first-generation
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Professor in AI-driven patient stratification and microbiome-based interventions (combined position)
data Explorative Network) , Odense University Hospital (OUH), respectively. The position is vacant as soon as possible, and the two 50% positions are considered as one entity (= full-time). Job
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of upstream and downstream processes. Integrate techno-economic and resource efficiency data into environmental modelling Analyse sustainability trade-offs, circularity potentials, and scenario-based system
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we expect: Qualifications The candidate must have a PhD degree at the time of employment. We value candidates who combine strong experimental skills with an ability to integrate data-driven approaches
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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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tasks include planning, conducting, and publishing epidemiological studies using large-scale observational data, primarily register-based, focusing on women’s short- and long-term health outcomes within