52 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" research jobs at Aarhus University
Sort by
Refine Your Search
-
polar orbit, passing near the poles about 15 times per day and regularly observing the CIFAR study region. Its payload - two optical cameras, a thermal camera, and onboard machine-learning capabilities
-
The Daasbjerg research group at the Department of Chemistry, Aarhus University, is seeking a candidate for a 31-month postdoctoral position. This position focuses on AI/machine learning to develop a
-
: http://international.au.dk/research/ The Danish School of Education The Danish School of Education at Aarhus University is Denmark’s largest centre for research and teaching in the fields of education
-
the Ph.D. candidate is enrolled as a Ph.D. student at Aarhus University Graduate School of Health ( http://phd.health.au.dk/ ) in a separate procedure before starting as a Ph.D. student. The successful
-
cultural events including music festivals etc. See e.g. the recent recommendation by CNN (https://edition.cnn.com/travel/article/aarhus-denmark-things-to-do/index.html). Aarhus is easily reached through
-
and technical-administrative staff and you have a flair for establishing collaborative relationships. Read more about the Department of Food Science at: https://food.au.dk/ The place of work is
-
, Belgium, and Germany, and offers the successful candidate excellent opportunities for interdisciplinary training, exchange, and scientific collaboration. Plant-PATH homepage: https://mbg.au.dk/plant-path
-
development for postdocs at AU. You can read more about it here: https://talent.au.dk/junior-researcher-development-programme/ If nothing else is noted, applications must be submitted in English. The
-
, electrical engineering, etc. Prior experience in (1) image processing, particularly for radiographic and computed tomographic data as well as mesh-type data, and (2) machine learning, particularly deep
-
qualifications include: Ph.D. in Computer Science, Computer Engineering, Electrical Engineering or a related field; Strong background in Deep Learning (e.g., Transformers, foundation models); Strong programming