Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Oslo
- University of Bergen
- UiT The Arctic University of Norway
- University of Agder
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- University of South-Eastern Norway
- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
- University of Stavanger
-
Field
-
effectively exploited, possibly using some kind of machine learning algorithm, provides more accurate data than traditional data collection methods, e.g. paper-based surveys. This data is valuable to several
-
that integrate prediction and control algorithms, optimizing data transformations, offloading and distributed computing, and exploiting mechanisms such as network slicing and multi-access edge computing
-
. The interdisciplinary center integrates researchers with substantive expertise from education, psychology, sociology, economics, and genetics, and methodological expertise from educational measurement, psychometrics
-
algorithms (including a description of practical work / projects / courses where this was used) skills you would need to develop deliverables of the project Your preliminary project proposal, in font size 12
-
to research on some of the following themes: New algorithms for parallel/distributed AI/ML Hardware-aware and resource-efficient partitioning for parallel/distributed AI/ML Optimization of process-to-process
-
physical latency limits and human perceptual tolerances. The work will comprise designing networking and computing architectures that integrate prediction and control algorithms, optimizing data
-
for testing newly developed algorithms is anticipated in mainland Norway, Svalbard, and abroad. Funding is also available for conference attendances and research visits with external collaborators. The position
-
on the development of machine learning algorithms, particularly transfer and adaptive learning, for multimodal wearable biosensing and its translation to rehabilitation and digital health applications. It is co
-
. The project is supervised by Associate Professor Ulysse Côté-Allard at the Department of Technology Systems, University of Oslo, whose research focuses on the development of machine learning algorithms
-
cytosolic adapters modulate the phosphoproteome of T cells, using high end mass spectrometry approaches, as well as immunological and genetic techniques. The research fellow must take part in the faculty’s