47 computational-physics "https:" "https:" "https:" "https:" "Caltech" Postdoctoral positions at Aarhus University
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at the Department of Physics. The position is available from the 1st of May 2026, or as soon as possible hereafter. Job description Your research will look at a special class of porous metal-organic frameworks (MOFs
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The project will involve both experimental and computational work and the candidate is expected to be comfortable with both. The candidate is expected to have (or be close to finishing) a Ph.D. in molecular
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and technical-administrative staff and you have a flair for establishing collaborative relationships. Read more about the Department of Food Science at: https://food.au.dk/ The place of work is
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information about the application process, please contact HR support at iks-hr-sag@au.dk . The workplace will be at Institute for Culture and Society, Aarhus University, Jens Chr. Skous Vej 5, 8000 Aarhus C
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@au.dk) Applicants must have a relevant PhD degree in biology, biogeochemistry, hydrology, glaciology, oceanography, geoscience or physics. Field experience, data analysis and programming (e.g., python
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graph algorithms for optimization under physical constraints Applying graph mining and graph data management techniques Designing computational methods for waste heat reuse and green transition goals
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This is a full-time (37 hours/week) on-site role located at Åbogade 34, 8200 Aarhus N, Denmark for a Postdoctoral Fellow at the Department of Computer Science, Aarhus University. The postdoctoral
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will report to Professor of Medical Physics Stine Korreman. Your competences You have academic qualifications at PhD level, for example within the following areas; computer science, biomedical
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development for postdocs at AU. You can read more about it here: https://talent.au.dk/junior-researcher-development-programme/ If nothing else is noted, applications must be submitted in English. The
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spatially explicit process-based ecological model (DEB-IBM) for muskoxen in the high-Arctic through the analyses of long-term GPS and acceleration data. using the model to estimate the (cumulative) impacts