59 assistant-professor-computer-science PhD positions at Technical University of Denmark in Denmark
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We need to reduce climate impact by replacing fossil fuel. In this PhD project you can help with the green transition by enabling widespread use of alternative fuels. As biofuels and e-fuels will be
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programme, please see DTU's rules for the PhD education . Assessment The assessment of candidates will be performed by Professor Bengt Johansson, Project leader of the AI controlled engine project and future
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engineering, statistics, physics, mathematics, data science, informatics or similar degree with an academic level equivalent to a master's degree. The candidate should preferably have: Dedication and the desire
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, electronics, and neuromorphic computing. You will join an international collaboration between DTU, EPFL, and Max Planck, gaining unique opportunities to work at the intersection of materials science, physics
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the research group Bioactives Analysis and Applications, and as part of the prestigious Alliance PhD program, you will collaborate with the Technical University of Munich (Germany). If you're ready to
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at the intersection of regeneration and entrepreneurship? If so, this PhD position in Regenerative Entrepreneurship may be the right opportunity for you. The Centre for Technology Entrepreneurship (DTU Entrepreneurship
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Job Description The Transport Division of the Department of Technology, Management and Economics (DTU Management) at the Technical University of Denmark (DTU) invites applications for a 3-year PhD
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of operating zinc-air batteries. Use automated Rietveld refinement for analysis of large data sets and Computed Tomography analysis of the imaging data. Dissemination of research results. Qualifications expected
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Job Description Are you ready to use data and engineering to change how industries manage complex systems? At DTU Construct, we offer you the chance to pursue a PhD that bridges cutting-edge
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candidate in the Acoustic Technology group at DTU Electro, you will conduct fundamental research in statistical signal processing and machine learning for microphone arrays, addressing real-world challenges