Sort by
Refine Your Search
-
The Department of Agroecology at Aarhus University, Denmark, is offering a postdoctoral position in machine learning for advanced peatland mapping, starting 01-12-2025 or as soon as possible
-
combines neuroscientific, musicological and psychological research in music perception, action, emotion and learning with the potential to test prominent theories of brain function and to influence the way
-
research and teaching environment and activities. We expect you to teach and supervise students at Bachelor’s and Master’s level and to carry out research of the highest international standards, which
-
learning and study environment, which is closely integrated in the research environment. Our department has unique and advanced animal experimental research facilities and technologies, situated in close
-
project. Your profile We are looking for a highly motivated candidate with a background in machine/deep learning, and communication networks. The required qualifications include: PhD in computer engineering
-
Post-Training Techniques: Exploring and designing post-training strategies (e.g., Supervised Fine-Tuning, Reinforcement Learning, or novel alignment protocols) targeting Danish and other Nordic languages
-
feed processing. For non-Scandinavian candidates an effort to learn to read, write, and speak Danish is a requirement. Contact Further information on the position may be obtained from Professor Jan Værum
-
. theses at the interface between structural engineering and machine learning. You will disseminate your research through peer-review publications and participation in international conferences. You will
-
understand how materials interact with soft and hard tissue. Willingness to learn and integrate new methods or technologies, such as bioinformatics and 3D imaging processing. Ability to work both independently
-
patterns, and extreme climate events remains a subject of debate. Using a combination of climate modelling, statistical methods, and machine learning, ArcticPush aims to uncover the conditions under which