Sort by
Refine Your Search
-
Category
-
Program
-
Employer
- NTNU - Norwegian University of Science and Technology
- University of Oslo
- University of Stavanger
- NTNU Norwegian University of Science and Technology
- University of South-Eastern Norway
- University of Bergen
- Oslo Metropolitan University
- Oslo University Hospital
- OsloMet
- The Norwegian School of Sport Sciences
- UiT The Arctic University of Norway
- 1 more »
- « less
-
Field
-
include, but is not limited to, UHPC material design and optimization, durability testing under harsh environmental conditions, fabrication and full-scale structural testing of sleepers under static and
-
performance concrete (UHPC). The project aims to develop and validate durable UHPC sleeper solutions that can improve structural performance, reduce maintenance needs, and extend the service life of railway
-
the future? PhD research fellow in "Distributed Optimization and Control of Reactive Power" Apply for this job See advertisement Welcome to USN The University of Southeastern Norway (USN) ranks as the
-
renewable energy use, energy security, and the reliable operation of hydro-dominated power systems. The project will focus on how AI can support advanced optimization models for hydropower and energy-system
-
for 3 years. Responsibilities The successful candidate will: Develop, optimize and validate advanced 3D cell culture models, including spheroids, organoids and tissue-engineered constructs. Establish
-
companies. The research will integrate techniques of numerical analysis and structure-preserving algorithms to generative modeling in AI. It will build upon the work done at IMF and SINTEF in this field. We
-
data-driven learning and which should remain within structured optimization. In line with AID’s research areas, the project will emphasize knowledge embedding, uncertainty representation, risk-aware
-
surgery. However, the growing use of TAVI has also increased the need for accurate methods to assess valve disease, identify patients who will benefit from intervention, determine the optimal timing
-
photovoltaic generation, hydrogen production, and storage alternatives with microgrid-driven power distribution. Through advanced modelling and optimization techniques, this research aims to identify optimum
-
capacity available to power markets with flow-based market coupling. Developing methods for optimally allocating the additional transfer capability enabled by increased transformer loading limits across day