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of turbulence while supporting industrial partners in accelerating the green transition and the digitalization of society within fluids engineering. For more information about the group’s work, see: Fluid
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for an interview may be asked to provide professional references. The application must be submitted in either English or Danish. For further information about the position and the project, please contact: Professor
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performance of other duties. Further information on the Department is linked at chem.ku.dk. Inquiries about the position can be made to the main supervisor. The position is open from January 1st 2027 or as soon
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addition, a tool capable for determining the Carbon Dioxide Removal (CDR) credits as a function of feedstock, location, pyrolysis process and technology and will be validated by real-world data. You will be
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postdoctoral researcher to join an interdisciplinary team developing deep learning models for antimicrobial resistance (AMR) detection directly from MALDI-TOF mass spectrometry data. The project is funded
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analyze interviews with company representatives, trade unions, labour inspectors and other authorities, and experts. Gather and analyze supplementary data such as statistics, archival data, media sources
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can find more information about the postdoc positions available in the areas listed here: https://math.au.dk/en/about/vacancies/postdoc/ When applying, you will be asked to indicate, which of the areas
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colleagues in the group and external partners in Denmark and abroad. You will work with the design and execution of research studies, the analysis and interpretation of data, and the dissemination of results
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the platform by embedding/developing additional tools for data processing and analysis. The starting point for the developments will be our EasyNMR platform (see easynmr.pastis.dk ). Current application areas
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groups work in close daily collaboration and share research infrastructure, methodological expertise, and a commitment to high-quality population-based epidemiology using Danish and Nordic register data