Sort by
Refine Your Search
-
Listed
-
Country
-
Field
-
to the computational modelling efforts at the Materials Theory Group. We are seeking a candidate with a strong background in artificial intelligence and machine learning, applied to condensed/soft matter physics
-
, 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
-
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
-
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
-
at the Norwegian University of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Documented knowledge and experience with machine learning or other relevant
-
of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Documented knowledge and experience with machine learning or other relevant AI Documented knowledge in
-
analyses, machine learning algorithms, structural equation modeling). A good practical knowledge of R Personal characteristics To complete a doctoral degree (PhD), it is important that you are able to: Work
-
. The objective of the research is to use machine learning methods to find models of ship trajectories and traffic patterns that can be used to detect anomalies and predict into the future. The basis for this is
-
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
-
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