Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
- University of Oslo
- Norwegian University of Life Sciences (NMBU)
- University of Bergen
- Western Norway University of Applied Sciences
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- NORCE Norwegian Research Centre
- UNIS
- University of South-Eastern Norway
-
Field
-
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
-
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
-
spanning a broad range of research areas in biostatistics, machine learning and epidemiology and numerous collaborations with leading bio-medical research groups internationally and in Norway. OCBE is a
-
is internationally recognized, with interests spanning a broad range of areas - including statistical machine learning, high-dimensional data and big data, computationally intensive inference
-
complex biological systems. Research Environment & Collaboration The successful candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable
-
& Collaboration The successful candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable implementations. By establishing a new class of multi-frame
-
candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable implementations. By establishing a new class of multi-frame factorization methods
-
invites applications for a PhD position focused on developing a theoretical framework for monitoring and updating adaptive learning systems (including machine learning/artificial intelligence systems) under