75 data "https:" "https:" "https:" "https:" "Dr" "UCL" Postdoctoral positions at Aarhus University in Denmark
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activities are project-based with a solid tradition in cross-disciplinary research and international collaboration. Job description The postdoctoral researcher will work with Dr. Robert Ladwig on developing
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the Entomology and Plant Pathology and Microbiology (PLANMIK) section. More information can be obtained from Dr. Ella Sieradzki, ellasiera@agro.au.dk Application procedure Shortlisting is used. This means
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part of the research groups of Drs. Lars Angenent and Alfred Spormann in a joint collaborative project, which also includes Prof. Bruce Logan of Penn State University. We are seeking highly talented and
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, close working relations, network activities among young scientists, and social activities a workplace characterized by professionalism, equality, and a healthy work-life balance Contact Information
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reference If you want a referee to upload a letter of reference on your behalf, please state the referee’s contact information when you submit your application. We strongly recommend that you make
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: Establish and develop experimental protocols and pipelines and implement data management compliance. Presentation of your work in various meetings (locally at the department, national and international
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University with related departments. Contact information For further information, please contact Prof Kim Daasbjerg at +45 23 48 52 49 or kdaa@chem.au.dk or alternatively Associate Professor Behzad Partoon
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, which is a collaboration between the Department of Business Development and Technology and the Department of Digital Design and Information Studies. The project ‘Practice Resonant AI Ethics for the Public
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information For further information, please contact: Professor Torben Heick Jensen, thj@mbg.au.dk, phone +45 60202705 Application procedure Shortlisting is used. This means that after the deadline
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main areas of work: Exploration of heterogeneity in GDM risk and GDM subtypes and application of these insights to develop a GDM risk prediction model, based on data from The Danish Blood Donor Study