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systems We offer A position in a vibrant, interdisciplinary research environment with strong industry links Access to state-of-the-art research facilities and real industrial data Opportunities
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Job Description We invite applications for a 3-year PhD scholarship at DTU Energy. The project will integrate innovative physics-based atomistic modeling methods and data-driven inverse molecular
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Job Description Are you passionate about transforming food safety through cutting-edge technology and want to apply your data science and AI skills to real-world public health challenges? This is
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PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
capital facility maintenance operations. The virtual education and training environment incorporates Digital Twin Construction project data, multimodal and augmented tools for realistic haptic control and
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28 Aug 2025 Job Information Organisation/Company Graduate School of Arts, Aarhus University Department Faculty of Arts Research Field Arts Researcher Profile First Stage Researcher (R1) Positions
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28 Aug 2025 Job Information Organisation/Company Graduate School of Arts, Aarhus University Department Faculty of Arts Research Field Arts Researcher Profile First Stage Researcher (R1) Positions
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28 Aug 2025 Job Information Organisation/Company Graduate School of Arts, Aarhus University Department Faculty of Arts Research Field Arts Researcher Profile First Stage Researcher (R1) Positions
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PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
2 Sep 2025 Job Information Organisation/Company Technical University Of Denmark Department DTU Civil and Mechanical Engineering Research Field Engineering » Civil engineering Engineering
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1 Sep 2025 Job Information Organisation/Company Technical University Of Denmark Department DTU Physics and DTU NanoLab Research Field Physics » Quantum mechanics Technology » Nanotechnology
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hiring date is as early as December 1, 2025, but can be anytime in 2026. The PhD student is expected to develop and apply statistical methodology for causal inference in observational and experimental data