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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
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can read more about career paths at DTU here . Further information Further information may be obtained from professor Poul Sørensen, email posq@dtu.dk , mobile phone +45 2136 2766. You can read more
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. The allowance will be agreed upon with the relevant union. The period of employment is 1 year and 10 months. You can read more about career paths at DTU here . Further information Further information may be
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. Place of work The place of work is Langelandsgade 140, 8000 Aarhus C, and the area of employment is Aarhus University with related departments. Contact information Further information about the position
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central experimental role in the project and work closely with a dedicated postdoc supporting advanced computational analysis and interpretation of data. The position offers substantial scientific
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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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research collaborations, experience with survey data collection in- and outside Denmark will be an advantage as well as the ability to write and communicate fluently in Danish and English Experience with
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-of-the-art methodology in endogenous protein editing and tagging by CRISPR and integrase strategies. Training in state-of-the-art technologies and data analysis as well as research management, oral and written
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Job Description We at the Hearing Systems Section are offering a postdoctoral research position in auditory science, motion behaviour, data analysis, and/or human communication. You will contribute