36 data-"https:" "https:" "https:" "https:" "https:" "https:" Postdoctoral positions at Nature Careers in Denmark
Sort by
Refine Your Search
-
further information are invited to contact Associate Professor Niculina Musat (niculina.musat@bio.au.dk). Who we are The successful candidate will be employed by the Department of Biology at Aarhus
-
utilizes the world-class Danish registries as well as international data sources to assess pharmacological questions in large populations. The environmental medicine group studies the impact of early life
-
optimizing color selection for attentional purposes. The successful candidate will be required to design, program and conduct EEG-experiments, analyze and interpret EEG and behavioral data and present results
-
unified data framework for microbial carbon dioxide conversion, integrating data from methanogens, acetogens, and hybrid projects for standardization, kinetic/thermodynamic measurements, and predictive
-
Information For further details about the position, please contact Professor Vijay Tiwari at tiwari@health.sdu.dk Application deadline January 11, 2026, at 23:59 hrs. CEST Apply online: https://fa-eosd
-
here . Further information Further information may be obtained from Carlos Acevedo-Rocha: cargac@biosustain.dtu.dk Google Scholar profile: https://scholar.google.com/citations?hl=en&user=yZDS88IAAAAJ
-
quality and functioning, particularly in plumes near river outlets. This post doc project will rely on existing data as well as new field data of nutrients, carbon, and stable isotopes from riverine-coast
-
analytical methods to large data sets The possibility for contract extension Flexibility in planning working hours Advanced professional training opportunities Possibility of participation in international
-
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
-
biology, epidimological data and AI-driven systems modeling. The successful candidate will develop and apply computational and machine learning approaches to decode the molecular and epigenetic mechanisms