Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- University of Oslo
- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
- UiT The Arctic University of Norway
- University of Bergen
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- University of Agder
- University of Stavanger
- NORCE Norwegian Research Centre
- Norwegian University of Life Sciences (NMBU)
- OsloMet
- University of South-Eastern Norway
- Østfold University College
- 3 more »
- « less
-
Field
-
modules, reasoning over structured graphs or rules, act as a factual verifier. The PhD fellow will perform the following tasks: Framework Design & Implementation, Reasoning Algorithms Development, and
-
of Materials, analytical and numerical Data-Driven Engineering Design and Optimization Algorithms Surrogate Modeling (e.g., Kriging, Gaussian Processes, Neural Networks, etc.) Scientific Programming (e.g
-
. Any appointment is conditional upon submission of documentation confirming completion of the PhD degree. solid programming skills applied to machine learning algorithms, interactive systems, audio and
-
of Computer Science We are the leading academic IT environment in Norway, and offer a wide range of theoretical and applied IT programmes of study at all levels. Our subject areas include hardware, algorithms, visual
-
new deep learning algorithms for spatio-temporal medical image analysis with particular focus on learning from limited labelled data. Start date: Fall 2026 Duration: The appointment is for 3 years It is
-
candidate with a background in SAR/InSAR signal processing and time series algorithms, combined with strong expertise from an application domain that strengthens the group’s current activities. Key
-
a PhD student, you will develop state-of-the-art learning and inference methods to detect and characterize anomalous radio behavior and to design algorithms that remain reliable under practical
-
a PhD student, you will develop state-of-the-art learning and inference methods to detect and characterize anomalous radio behavior and to design algorithms that remain reliable under practical
-
-based methods to achieve personalised and novel outputs. This position will have a particular focus on developing fundamental AI algorithms and methods that can be used in systems for real-time creative
-
in marine cybernetics Background in marine hydrodynamics Background in the application of probabilistic methods Experience with the application of AI algorithms Good programming skills Personal