35 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" Postdoctoral positions at Nature Careers in Denmark
Sort by
Refine Your Search
-
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
-
, and offers the successful candidate excellent opportunities for interdisciplinary training, exchange, and scientific collaboration. Plant-PATH homepage: https://mbg.au.dk/plant-path Place of work and
-
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
-
unified data framework for microbial carbon dioxide conversion, integrating data from methanogens, acetogens, and hybrid projects for standardization, kinetic/thermodynamic measurements, and predictive
-
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
-
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
-
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
-
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