Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Oslo
- NTNU - Norwegian University of Science and Technology
- UiT The Arctic University of Norway
- University of Bergen
- University of Stavanger
- NTNU Norwegian University of Science and Technology
- CICERO Center for International Climate Research
- CMI - Chr. Michelsen Institute
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- OsloMet - storbyuniversitetet
- OsloMet – Oslo Metropolitan University
- Simula UiB
- University of Agder
- University of Oxford
- Østfold University College
- 5 more »
- « less
-
Field
-
at http://www.icgi.no and http://www.domore.no. The position is based in the Digital Signal Processing and Image Analysis group (DSB), Section for Machine Learning, at IFI. DSB has seven full-time and five
-
topics include (a) AI, machine learning, and large language models for measurement challenges (e.g., for small-sample calibration or for accelerated algorithms), (b) identifying and investigating aberrant
-
research activity. In this project, you will develop fundamental machine learning methods and apply them in an interdisciplinary research environment spanning physics, neuroscience and computational science
-
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
-
modelling knowledge, incorporate reliability/uncertainty, and/or explainable models. The position is in the Digital Signal Processing and Image Analysis Group, Section for Machine Learning, Department
-
representations developed in them as a foundation for this research activity. In this project, you will develop fundamental machine learning methods and apply them in an interdisciplinary research environment
-
operationally safe position in real-time. This research focuses on real-time multi-objective optimization of wells, that may be achieved with a mixture of algorithmic and machine-learning approaches. Updating
-
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
-
: OUH - Cell and tissue dynamics (Bøe) Project description GENESIS is a newly established Life Science Convergence Environment that brings active matter physics, cell biology, and machine learning
-
. The core research objective of this PhD is to design and evaluate “latency hiding” methods for immersive networked interactions. This involves (i) developing predictive machine learning models that forecast