59 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"KU-LEUVEN" positions at Nature Careers in Denmark
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50% are scientific staff. More information can be found here . We believe in encouraging inclusion, acceptance, and understanding by employing staff who bring unique perspectives to our department
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employees, of which approximately 50% are scientific staff. More information can be found here . We believe in encouraging inclusion, acceptance, and understanding by employing staff who bring unique
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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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responsible for all data analysis. You will report to the Head of Department of Biomedicine. Your competences Successful candidates will have an excellent track record and will be highly motivated, self-driven
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sections with around 350 highly skilled employees, of which approximately 50% are scientific staff. More information can be found here . We believe in encouraging inclusion, acceptance, and understanding by
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researcher network. The department consists of nine research sections with around 350 highly skilled employees, of which approximately 50% are scientific staff. More information can be found here . We believe
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Tenure-track Assistant/Associate Professor/Professor in Ecophysiology and Ecology Department of B...
methodologies. Further information For additional information please contact Head of Section for Aquatic Biology Professor Tenna Riis (tenna.riis@bio.au.dk) (position 1), Head of Section for Microbiology
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analysis to extract information on atomic dynamics from image series. Investigate molecular adsorption, surface reconstruction and site-dependent reactivity at the single-atom level Understanding of atomic
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Postdoctoral Researcher Position in Ecological Knowledge-Guided Machine Learning at Aarhus Univer...
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
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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