Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- University of Oslo
- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
- University of Bergen
- UiT The Arctic University of Norway
- Norwegian University of Life Sciences (NMBU)
- OsloMet
- University of Stavanger
- University of South-Eastern Norway
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- Western Norway University of Applied Sciences
- CMI - Chr. Michelsen Institute
- NORCE Norwegian Research Centre
- Nansen Environmental and Remote Sensing Center
- Norwegian Meteorological Institute
- Simula Research Laboratory
- Simula UiB
- UNIS
- University of Agder
- Østfold University College
- 10 more »
- « less
-
Field
-
hazards, enhancing asset protection, maritime security, emergency preparedness, and societal resilience. The project will leverage advanced AI and machine learning techniques to enable predictive risk
-
complementary and synergic methods at the intersection of Artificial intelligence, Machine learning, Numerical simulation, Formal verification. Such methods include, among the others: AI-guided simulation
-
. You will become part of a dynamic, collaborative working environment with expertise in drilling engineering, geomechanics, machine learning, and energy systems. The project will integrate real‑time
-
optimization (WOB, RPM, flow rate, etc.) using machine learning techniques Anomaly detection for downhole vibrations, bit failure, and circulation losses Integrating physical modeling, digital twins, and data
-
and accelerate the development of more high-performing PNSEs. The ultimate goal of the project is to develop, implement, and validate novel deep-learning models for molecular dynamics and coarse-grained
-
for a period of four years are expected to acquire basic pedagogical competency during their fellowship period within the duty component of 25 %. Project description and work tasks Particle accelerators
-
information science at the Bachelor and Master levels. This may include courses in information science foundations, programming, artificial intelligence, machine learning. In addition, the candidate is expected
-
an advantage if you have Interest in the mechanical behavior of materials. Experience with machine learning and/or programming/coding. Experience with finite element modeling from civil, mechanical, or marine
-
representations developed in them as a foundation for this research activity. In this project, you will develop fundamental machine learning methods and apply them in an interdisciplinary research environment
-
-state model will be approximated using machine-learning surrogates and will be used for a real-time optimization, such that the plant operates optimally despite disturbances. The candidate will be part of