Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
the application process can be completed in the Aarhus University system without uploading publications or a teaching portfolio, applications that do not include uploaded publications (a maximum of five) and a
-
26306659 Simon.wall@phys.au.dk Application procedure Shortlisting is used. This means that after the deadline for applications – and with the assistance from the assessment committee chairman, and the
-
(preferably with Python). Application procedure Shortlisting is used. This means that after the deadline for applications – and with the assistance from the assessment committee chairman, and the appointment
-
93 50 83 45, edrazevic@bce.au.dk . Deadline Applications must be received no later than 30th April 2026. Application procedure Short-listing is used. This means that after the deadline for applications
-
tasks, including but not limited to: Experimental work related to processing press cake and derived polymers into textile filaments Preparation, handling, and characterization of polymerbased and bio
-
, education and society. Develop Science Bridge as a new organisational unit, including defining structures, processes, and ways of working, and ensuring a strong and coherent operational foundation
-
about PACE here . About the research project Candidates will be part of a research group investigating the immune system in the neurodegenerative process in Parkinson’s disease. The candidate will use
-
developments within the field, including plans for publications, funding applications and collaborations with external partners. Please note that although the application process can be completed in the Aarhus
-
Region. We have approx. 30,000 square metres of modern research facilities for experimental surgery and medicine, animal facilities and also advanced scanners at our disposal. The department has overall
-
Join us at the Department of Electrical and Computer Engineering at Aarhus University for a postdoctoral position focused on deep learning based analysis of remote sensing data for groundwater