31 parallel-processing-bioinformatics "Multiple" Postdoctoral positions at Aarhus University in Denmark
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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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Munkegade 118, 8000 Aarhus C. For questions or further information, please contact Christoffer Basse Eriksen (cbe@css.au.dk). Application procedure Shortlisting is used. This means that after the deadline
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If you need help uploading your application or have any questions about the recruitment process, please contact HR supporter Ulla Prisholm Bjørn Tel.: +45 87152179 Email: upb@au.dk. Place of work The place
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, including: Participate in the design and detailed engineering phases of up-scale microbial electrochemical reactors. Support commissioning, operation and testing of the up-scale microbial electrochemical
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processes and nanomaterial functionalization. Comprising around 20 members - including PhD students, postdocs, and technical staff - the group fosters a collaborative, interdisciplinary environment focused
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aerosol modules, and assess the importance of different processes with a comparison to available observations. Analyse large model output and observational datasets to determine the impacts and main drivers
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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
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nicolaivoneggers@cas.au.dk For further information about the application procedure, please contact HR supporter Gerd Bech Thomsen (gebeth@au.dk ) The work environment Researchers at the Department of History work
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these issues. The center brings together experts on climate impact research and process-based modelling of biogeochemistry, agronomy, biology and geography from Aarhus University and University of Copenhagen, as
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Science, Computer Engineering, Artificial Intelligence, Physics, Mathematical Engineering, Mechanical Engineering or similar. Relevant skills: Strong background in machine learning/data science. Deep knowledge