226 data "https:" "https:" "https:" "https:" "UNIV" positions at Technical University of Denmark
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to assess and interpret data from experiments, with the ability to identify trends, troubleshoot issues, and optimize processes. Experience in critical evaluation and troubleshooting of both process
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like additional information about the position, please contact head of team Mattias Andersson on 93 51 18 01. To learn more about the department, visit DTU Wind . Please note that applicants may be
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online application no later than 15 March 2026. Open the “Apply now” link, fill out the form and attach your motivated application, CV and exam certificates. If you would like additional information about
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evaluation using nasal epithelial models and tissue Contribute to in vivo validation in an established mouse model of acute seizures Analyze pharmacokinetics, biodistribution, and therapeutic efficacy data Co
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industry-facing research collaboration and coordinate cross-partner workflows in planning, data-sharing, and iterative decision-making across industrial and academic stakeholders. Teach and supervise PhD
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authorities, and the other DeiC departments working with quantum computing and data management. We help facilitate Danish researchers’ access to the LUMI supercomputer, which ranks in the Top 10 fastest in
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employment is 21 months. Expected starting date is 1 June 2026, or according to mutual agreement. You can read more about career paths at DTU here . Further information Further information may be obtained from
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, or according to mutual agreement. The working location will be DTU Construct, Lyngby Campus. You can read more about career paths at DTU here . Further information Further information may be obtained from Senior
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paths at DTU here . Further information Further information may be obtained from Professor Julia Kirch Kirkegaard (jukk@dtu.dk ) and/or Section Head Tanja Schneider (tansch@dtu.dk ). You can read more
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assessment. Design and train reinforcement learning agents to optimize operational safety. Build and validate dynamic Bayesian network models integrating empirical and synthetic data. Conduct scenario-based