20 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" PhD positions in Norway
Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
, target recognition and shape estimation, data association, as well as intention prediction, beyond the state of the art. In order to support machine learning, the project will make use of historical radar
-
democracy, our centre tackles the promise and peril of hybrid intelligence—humans and machines working and learning together. Our mission is to establish an internationally leading interdisciplinary hub
-
collaborations across Norwegian universities, research institutes, industry, public agencies, and leading global institutions. We welcome motivated applicants in robotics, control, AI, machine learning, physics
-
calculations Knowledge about machine learning application in condensed matter Knowledge about magnetism, superconductivity, and topological order Personal characteristics We are looking for a candidate who is
-
research and academic bodies. This collaboration is centered around a unique, open-source digital platform enriched with data and powered by domain knowledge-based advanced machine learning and artificial
-
mixed models, permutational methods, Bayesian analyses, machine learning algorithms, structural equation modeling). A good practical knowledge of R Personal characteristics To complete a doctoral degree
-
, 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 embodied AI
-
. We welcome motivated applicants in robotics, control, AI, machine learning, physics, and related fields, including early-stage researchers eager to contribute to this emerging scientific frontier
-
centered around a unique, open-source digital platform enriched with data and powered by domain knowledge-based advanced machine learning and artificial intelligence capabilities. By introducing a Digital
-
, currents, water levels, wind, and ice. Machine learning models will be developed to forecast future variations in such dynamic conditions and to incorporate the operational state of the vessel into routing