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position is available from 1 February 2026. The research project King Frederik Center for Public Leadership aims to provide better knowledge about how leadership can improve motivation and performance in
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fostering a creative and successful academic environment. DTU Electro has 350 employees and span activities in physics, photonics, and electrical engineering. Research is performed within nanophotonics
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Senior Researcher in Synthetic Biology and Metabolic Engineering of power-to-X utilizing Microorg...
If your goal is to lead groundbreaking research and make a real-world impact, DTU Biosustain offers the perfect launchpad. Join us and redefine what’s possible in sustainable science and innovation
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(Danish, Swedish and Norwegian), to effectively engage with stakeholders, citizens, public and the scientific community. Experience with the peer-review publication process is an advantage. You must have a
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manufacturing systems for subtractive manufacturing. Strong knowledge of process monitoring, manufacturing metrology, and programming tools such as Matlab is highly desirable. You should have good analytical
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algorithms. Graph Neural Networks. The candidate is expected to hold a relevant MSc degree in Computer Science, Data Science, Physics, (Applied) Mathematics, Computational Statistics or another field
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properties of the extracted compounds, (iv ) scale-up the optimized extraction process for potential industrial application. This is a unique opportunity to contribute to sustainable food innovation while
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, and characterization of such devices. Responsibilities and qualifications The focus of this position is to help advance the development of a reliable and efficient dual-fuel HT-PEMFC using multi-physics
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relation to extreme wealth. The position is part of the research project, The Morality of Extreme Wealth , funded by the Independent Research Fund Denmark and is available from 01-02-2026, or as soon as
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recent large-scale capabilities in physics. Reliability, exploring uncertainty quantification and robust inference in machine learning. Explainability, leveraging identifiability and unique recovery