153 data "https:" "https:" "https:" "https:" "Stanford University" positions at Aarhus University
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quality. Your main tasks will consist of: Conducting independent research of high international quality, including publication in leading journals Performing advanced spatial data analysis, including
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University. Dr Speed's research involves developing statistical methods for better analysing data from genome-wide association studies (GWAS), with a particular focus on improving our understanding of human
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Department of Management, please visit: http://mgmt.au.dk/ . Further information For further information about the position and the department, please contact Assistant Professor Gabriele Torma, email
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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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The Centre for Computational Thinking and Design at the Department of Digital Design and Information Studies within the School of Communication and Culture at Aarhus University invites applications
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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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with teamwork in a great team Additional information Your place of work will be the AU International Centre at Høegh Guldbergs Gade 4a in Aarhus. The position is paid according to state agreements. Who
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broad variety of services for international researchers and accompanying families, including relocation service and career counselling to expat partners. Please find more information here: https
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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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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