30 coding-"https:"-"Prof"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "https:" "I.E" Postdoctoral positions at Nature Careers in Denmark
Sort by
Refine Your Search
-
of personal background. Apply online https://fa-eosd-saasfaprod1.fa.ocs.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_1001/jobs/preview/3538
-
. The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background. Apply online https://fa-eosd-saasfaprod1
-
refer to http://mbg.au.dk/ for further information about The Department of Molecular Biology and Genetics and to https://nat.au.dk/ and http://www.au.dk/ for information on Faculty of Natural Sciences
-
. The Section for Wildlife Ecology is situated in Aarhus and employs 35 staff members, including six affiliated with the bat research group. For more information on the Department see: http://ecos.au.dk/en/ What
-
recommendation by CNN (https://edition.cnn.com/travel/article/aarhus-denmark-things-to-do/index.html ). Aarhus is easily reached via local international airports in Jutland within 1 hour of Aarhus, or via
-
engaged scientific environment at the Section for Arctic Ecosystem Ecology (for more information see: https://ecos.au.dk/en/researchconsultancy/research-areas/arctic-ecosystem-ecology ). The department is
-
19165 Post-Doctoral Fellowship in risk assessment and prioritization and remediation of dumped mu...
fishing activities, major shipping routes, and offshore development locations. The EU Oceans Pact highlight the need to assess and manage dumped munitions. Two EU-funded projects, MUNI-RISK (https://muni
-
Applications are invited for a postdoctoral position in the group of Dr Aleksandr Gavrin ( https://mbg.au.dk/a-gavrin/ ) at the Department of Molecular Biology and Genetics, Aarhus University
-
Postdoctoral Researcher Position in Ecological Knowledge-Guided Machine Learning at Aarhus Univer...
ecological processes, i.e., vertical turbulent diffusion, phytoplankton production and consumption, greenhouse gas emissions, etc., to develop hybrid models. Performance will be compared to several 1D aquatic
-
-constrained machine-learning (ML) models in simulations of turbulent flows. You are expected to contribute to research and development in data-driven methodologies for turbulence modeling in LES (i.e., wall and