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
- University of Stavanger
- Norwegian University of Life Sciences (NMBU)
- OsloMet
- University of South-Eastern Norway
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- Western Norway University of Applied Sciences
- CMI - Chr. Michelsen Institute
- NORCE Norwegian Research Centre
- Nansen Environmental and Remote Sensing Center
- Norwegian Meteorological Institute
- Simula Research Laboratory
- Simula UiB
- UNIS
- University of Agder
- Østfold University College
- 10 more »
- « less
-
Field
-
the Department). The position is financed by the University of Bergen. About the project/work tasks The PhD project aims to investigate how methods from Scientific Machine Learning (SciML) can enhance modelling
-
artificial intelligence. In a world where AI systems are reshaping how we learn, work and participate in democracy, AI LEARN tackles the promise and peril of hybrid intelligence—human and machine working and
-
at the intersection of deep learning and computer systems. The successful candidate will join an international and collaborative research environment and contribute to advancing efficient AI systems through close
-
universities, research institutes, industry, public agencies, and leading global institutions. We welcome motivated applicants in robotics, control, AI, machine learning, physics, and related fields, including
-
to work on cutting-edge research at the intersection of deep learning and computer systems. The successful candidate will join an international and collaborative research environment and contribute
-
, control, AI, machine learning, physics, and related fields, including early-stage researchers eager to contribute to this emerging scientific frontier. Duties of the position Fundamental contributions in
-
researchers. The centre is internationally recognized, with interests spanning a broad range of research areas in biostatistics, machine learning and epidemiology and numerous collaborations with leading bio
-
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
-
inventories and provision of environmental information. Similarly, the developments in AI and machine learning allow for new and improved processing of remotely sensed data supporting precision forestry
-
for 3 years. The project is conducted in close collaboration with the SFF Integreat, The Norwegian Centre for Knowledge-driven Machine Learning (ML) , a centre of excellence funded by RCN and in operation