Sort by
Refine Your Search
-
Category
-
Employer
- University of Oslo
- UiT The Arctic University of Norway
- University of Stavanger
- NTNU Norwegian University of Science and Technology
- University of Bergen
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- OsloMet - storbyuniversitetet
- OsloMet – Oslo Metropolitan University
- Simula Research Laboratory
- Simula UiB
-
Field
-
Signal Processing and Image Analysis group (DSB), Section for Machine Learning, at IFI. DSB has seven full-time and five adjunct positions and carries out research across image analysis and machine
-
Processing and Image Analysis Group, Section for Machine Learning, Department of Informatics. You will be part of Visual Intelligence and the DSB group. For more information about the position see https
-
functions to work properly. Please turn on JavaScript in your browser and try again. UiO/Anders Lien 1st March 2026 Languages English English English PhD Research Fellow in Machine Learning for Cognitive
-
hazards, enhancing asset protection, maritime security, emergency preparedness, and societal resilience. The project will leverage advanced AI and machine learning techniques to enable predictive risk
-
this by concentrating on five select research areas in ICT. Learn more about: working at Simula and careers at Simula Project/Job description In the Department of ComplexSE, we are now offering a
-
the Digital Signal Processing and Image Analysis Group, Section for Machine Learning, Department of Informatics. You will be part of Visual Intelligence and the DSB group. For more information about the
-
: Preference Learning for LLMs Apply for this job See advertisement About the position Integreat – the Norwegian Centre for Knowledge-driven Machine Learning at the University of Oslo – invites applications
-
research in various areas of mobile network systems, multimedia and AR/VR/XR systems, robotics and machine learning, focusing on fundamental aspects as well as on applications in multidisciplinary contexts
-
numerical models and machine learning tools to predict loads, assess structural responses, and identify damage under extreme conditions. By combining computational simulations with data-driven approaches
-
profile for their ideal candidates are described as follows. PREMAL is a project focused on privacy-preserving machine learning using FHE. The project will investigate trade-offs between accuracy, time, and