443 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"ISCTE-IUL" positions in Denmark
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Human Centred Computing Section invites applicants for a 2-year Post Doctoral Fellowship in Computer Supported Cooperative Work (CSCW) in the NeuroGen Computing research project focusing on creating
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Job Description In order to expand the Centre for Visual Data Science , the Department of Mathematics and Computer Science at the University of Southern Denmark, Odense, invites applications for a
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the Department of Electrical and Computer Engineering, please visit https://ece.au.dk/ . Visit our LinkedIn: https://www.linkedin.com/company/au-ece/ Research areas in the department Electrical and
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As research assistant, your primary tasks are full time laboratory work and data analysis. You contribute to the development of the department through research of high international quality. In your
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barriers and facilitators of prevention programs. The ideal candidate has a background in or experience with one or more of the following topics and areas: Survey methodology / Survey data analysis
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highly skilled and innovative Automation Specialist to meet the growing demands for advanced data handling and process automation, essential for data-driven discoveries and adherence to stringent research
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will be part of a research environment focusing on integrating multi-source satellite remote sensing data and developing novel algorithms to quantify agroecosystem variables for environmental
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Aarhus University with related departments. Contact information Before applying or for further information, please contact: Associate Professor Aurelien Dantan, +4523987386, dantan@phys.au.dk . Deadline
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, data management and analyses in an interdisciplinary research environment on Danish and international projects? You might then be the perfect candidate for one of our current vacancies. The Climate and
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on “ Integrating AI into Aquatic Ecosystem Models to Decode Ecological Complexity ” funded by Villum Fonden. Within that project, the focus is on exploring novel ways to infer information from environmental data