Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- University of Oslo
- UNIVERSITY OF SOUTHAMPTON
- University of Bergen
- Christian-Albrechts-Universitaet zu Kiel
- FCiências.ID
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- Nanyang Technological University
- OsloMet
- UiT The Arctic University of Norway
- University of Houston
- University of Minho
- University of Stavanger
- 2 more »
- « less
-
Field
-
laser experimentation to study and control complex nonlinear dynamics. Key Responsibilities: Develop and implement Physics-Informed Neural Network (PINN) models to simulate, predict, and analyze complex
-
Network HORIZON-MSCA-2024-DN-01 on Wind farm control and integration in sector-coupled power systems (WindConnect). This doctoral position is part of WindConnect ("Wind farm control and integration in
-
results of experiments or projects under control or supervisory responsibility. 2. Recommends changes in research, testing or experimental procedures. 3. May be responsible for a single highly technical and
-
of the following areas: robotics, machine learning, robot perception, underwater systems, nonlinear control, system modelling, or autonomous manipulation Strong programming skills and a solid
-
control the properties of the output laser beam and to focus it on the workpiece makes fibre lasers indispensable to modern manufacturing. As we enter the Digital Manufacturing/Industry 4.0 era however, new
-
of equivariant neural networks. Core motivating problems include: learning models governed by partial differential equations (PDEs) on nonlinear spaces, transfer learning between domains with different geometric
-
on inverse multiple-scattering algorithms. Implement and evaluate both linear approximation models and nonlinear high-order scattering approaches for accurate imaging of thick and strongly scattering
-
to precisely control the properties of the output laser beam and to focus it on the workpiece makes fibre lasers indispensable to modern manufacturing. As we enter the Digital Manufacturing/Industry 4.0 era
-
research environment at the University of Stavanger (UiS), in collaboration with three other foreign universities. It builds on previous work of evaluating existing NDT techniques and nonlinear fatigue
-
bold: develop cutting-edge digital solutions to drastically reduce Norway’s offshore emissions. To support the goals of CSSR, this project aims to develop, analyze and implement new nonlinear iterative