63 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions at Aarhus University
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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
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. Key responsibilities • Plan and execute daily mission operations • Operate and develop the ground segment • Coordinate calibration/validation activities and assure data quality • Manage
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April 2026 to 31 March 2027. The successful applicant will be responsible for data scraping and quantitative data analysis. The post will include data scraping of online content related to counter
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) outlining a research project addressing the history of Danish botany and the Flora Danica volumes in the period 1840–1900 within the statement of future research plans and information about research
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underlying greenhouse gas fluxes Support training of young researchers in using biogeochemical observations and data analysis Write and contribute to international peer-reviewed publications Contribute
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scientific journals Research experience in some of the areas of fungal transformation, CRISP/Cas9 modification of fungal genes, analysis of metabarcoding data, and soil microbiology. Additional qualifications
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departments. Contact information For further information, please contact: Dr., Peter Zeller, peter.zeller@mbg.au.dk Deadline Applications must be received no later than 23 February 2026. Application procedure
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analysis) Data collection, documentation, and basic data analysis Contribution to reporting, presentations, and potentially scientific publications Supporting collaboration within the research group and with
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research 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
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international 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