120 machine-learning "https:" "https:" "https:" "https:" "https:" positions in Norway
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
- Western Norway University of Applied Sciences
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- NORCE Norwegian Research Centre
- Norwegian University of Life Sciences (NMBU)
- OsloMet - storbyuniversitetet
- OsloMet – Oslo Metropolitan University
- Peace Research Institute, Oslo (PRIO)
- Simula UiB
- The Peace Research Institute Oslo (PRIO)
- 5 more »
- « less
-
Field
-
models with drone imagery using machine learning techniques and data assimilation. The work will involve collaboration with an interdisciplinary team of researchers, engineers, and local stakeholders in a
-
understanding of how acoustic waves are generated and transmitted in wells. The LeDAS project aims to overcome these challenges by combining physical modelling, advanced signal processing, and machine learning in
-
dissertated before the start-up date of the position. A research profile with relevant experience in biological sequence analysis, with complementary skills in machine learning or other relevant algorithms. A
-
promise and peril of hybrid intelligence—humans and machines working and learning together. Our mission is to establish an internationally leading interdisciplinary hub that advances foundational research
-
(ph.d.) in artistic development work at the Norwegian University of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Experience with machine learning
-
selection criteria Experience with machine learning or other relevant AI technologies Experience with condition monitoring, preferably within maritime domains Knowledge of ship machinery and systems Good oral
-
. Demonstrated experience applying machine learning and AI-based approaches to empirical disease, ecological, or biological datasets, with an emphasis on pattern identification, prediction, or spatial risk mapping
-
of Visual Intelligence is to develop novel, innovative solutions based on deep learning to extract knowledge from complex image data. Deep learning, aided by machine learning techniques in general, has led
-
implement new nonlinear iterative solvers, with the goal of exploiting models of various complexity, ranging from high-performance computing, via reduced-order models to data-driven (machine-learned
-
interest in social science applications, and with strong competence in statistics and machine learning. The successful candidate will develop predictive models using machine learning and work alongside other