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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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Science including quantitative and qualitative consumer research methodologies, and experience in designing consumer studies in and out-side Denmark. Solid experience in statistical analysis are preferred
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. Establish approaches to quantify the uncertainty in model outputs using different methods. Establish standardized methodology for greenhouse gas flux measurements Design field experiments to test processes
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as possible hereafter. For more information contact Professor Tenna Riis (tenna.riis@bio.au.dk) or Assist. Prof. Johnna M. Holding (johnna@ecos.au.dk). Post doc 2: Glaciers are melting
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international attention as a travel destination due to its unique combination of a thriving food-scene, high-quality museums, a surrounding beautiful nature, a very lively city due to the “young population”, many
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level, e.g. in medical physics, physics, biomedical engineering or computer science. It is mandatory that your PhD degree is on a topic relevant for this specific position, e.g. in medical image-based
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strong background in computational condensed matter physics. Experience with first-principles electronic structure methods and scientific programming is expected. The ideal candidate is highly motivated
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designs. Visit his group webpage (http://mbg.au.dk/yuya-hayashi/ ) for further information. Yuya also organises a cross-departmental network of extracellular vesicle researchers at Aarhus University, EVAnet
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within DanSIC and CIMP. Collaborate with internal and external researchers to design experiments and analyze complex datasets. Perform statistical analyses and data visualization to interpret and publish
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Postdoctoral Researcher Position in Ecological Knowledge-Guided Machine Learning at Aarhus Univer...
for environmental challenges, are also encouraged to apply. The postdoctoral researcher will work within an interdisciplinary team of computational and applied scientists. The work will be done in close collaboration