294 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Dr" "P" uni jobs in Denmark
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in the fields of: Construction Management and Lean Construction. Production Planning and Control. Data-driven analytics and management of construction operations. Construction Informatics, including
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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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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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on the platform ARTIQ (ARTIQ ) Application deadline The application deadline is the 1st of May 2026 Contact information Further information can be obtained from Michael Drewsen ( drewsen@phys.au.dk ) Formalities
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collaboration with Odense University Hospital ensures excellent possibilities for translational research. Information about the department and contact details to professors leading relevant research groups can be
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Applicants should have strong experience in one or more of the following overlapping areas: Analog and mixed-signal IC design: amplifiers, references, data converters, sensor interfaces, and power management
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in across biomes, species and methodologies. Further information For additional information please contact Head of Section for Aquatic Biology Professor Tenna Riis (tenna.riis@bio.au.dk) (position 1
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the EuroTeQ initiative at DTU by assisting with communication, event coordination, and data analysis related to student engagement and EuroTeQ educational offerings. The role involves collaboration with
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position is a full-time, fixed-term appointment as an assistant professor with a view to a permanent associate professorship (tenure), subject to a positive tenure review. Further information on the tenure
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international researcher network. The department consists of nine research sections with around 350 highly skilled employees, of which approximately 50% are scientific staff. More information can be found here