Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- University of Oslo
- NTNU Norwegian University of Science and Technology
- University of Bergen
- NTNU - Norwegian University of Science and Technology
- University of Stavanger
- UiT The Arctic University of Norway
- Norwegian University of Life Sciences (NMBU)
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- NORCE Norwegian Research Centre
- NORWEGIAN UNIVERSITY OF SCIENCE & TECHNOLOGY - NTNU
- Nord University
- The Peace Research Institute Oslo (PRIO)
- VID Specialized University
- 3 more »
- « less
-
Field
-
period at the University of Oslo. Place of work is Department of Informatics at Blindern, Oslo. Job description Unsupervised machine learning (ML) methods are widely used to explore structure in complex
-
fundamental insight into the structure-composition-function correlations that govern the performance of heterogeneous catalysts in reactions relevant to the Cyclic Carbon Economy: CO2 hydrogenation with green
-
Magnets for New Energy and MObility Applications“ funded by the European Union (ERC, MagNEO, 10522110, https://magneoproject.eu/ ). The project aims to develop new alloy material for permanent magnets
-
of the Center for integrative neuroplasticity (CINPLA) and in the INTED center. This PhD project will focus on reinforcement learning methods for generating complex structures with two possible application areas
-
arising from the inclusion of scrap, and to control the processing parameters such that the structural integrity of the cast components can meet with the demands to performance. The starting date is August
-
surfaces and when actively driving a soft sheet near a wall. Essential to the projects is developing a new understanding of the fluid-structure interactions, that is to say, the coupling between hair’s
-
: Digital twin development for heritage risk preparedness AI-based predictive monitoring (humidity, flooding, structural stress) Integration of GIS/BIM, LiDAR and IoT telemetry Federated data architecture and
-
machine learning (ML) methods are widely used to explore structure in complex and high-dimensional data, particularly in the life sciences, where clustering analyses often form the basis for biological
-
Technology . The position is for a period of 3 years. Desired start date: 1 May 2026 or earlier. The fellowship is part of TIES project “Tunable ion separations with micro-structured composite membranes
-
-funding from industry and academic partners. You can read more about NICE on https://www.ntnu.edu/nice. Duties of the position Complete the doctoral education until obtaining a doctorate Carry out research