Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- University of Oslo
- University of Bergen
- NTNU - Norwegian University of Science and Technology
- UiT The Arctic University of Norway
- University of South-Eastern Norway
- OsloMet
- University of Stavanger
- Norwegian University of Life Sciences (NMBU)
- Western Norway University of Applied Sciences
- Nature Careers
- University of Agder
- ;
- Nord University
- Molde University College
- Østfold University College
- NHH Norwegian School of Economics
- University of Inland Norway
- ; University of Dundee
- ; University of Oxford
- CICERO Center for International Climate Research
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- NORCE
- Norwegian Center for Violence and Trauma Stress Studies
- Norwegian Institute of International Affairs
- Norwegian Meteorological Institute
- The Norwegian Polar Institute
- UNIS
- 17 more »
- « less
-
Field
- Computer Science
- Economics
- Medical Sciences
- Social Sciences
- Biology
- Engineering
- Earth Sciences
- Materials Science
- Mathematics
- Linguistics
- Education
- Science
- Environment
- Humanities
- Chemistry
- Philosophy
- Psychology
- Physics
- Arts and Literature
- Electrical Engineering
- Law
- Business
- Sports and Recreation
- Statistics
- 14 more »
- « less
-
a single method for anisotropic flow modelling for both ice and olivine, by mapping CPO parameters directly to anisotropic viscosity parameters. This technique should reduce the computation complexity
-
-erklæringen var sist oppdatert 26.07.2025 Hva er en cookie? En cookie er en liten datafil som lagres på datamaskinen, nettbrettet eller mobiltelefonen din. En cookie er ikke et program som kan inneholde
-
contribute to the current teaching needs of the Faculty of Law, including the multidisciplinary master program in human rights . The purpose of the fellowship is research training leading to the successful
-
methodological capacities as well as documented expertise in computational methods. Experience with high performance computing is strongly preferred. Experience from applied work in change and anomaly detection is
-
level subject/master’s degree worth 120 ECTS in health sciences, kinesiology, or similar excellent working knowledge at master’s degree level of quantitative research methods and statistics experience
-
development of computer systems for data analysis, development of machine learning methods, and the clinical use of technology. Within the research groups you will therefore work together with computer
-
in-depth qualitative analyses but also mixed-methods approaches, possibly enabled by emerging AI-enhanced techniques. The PhD project should overall contribute to a better understanding collaborative
-
-prediction benchmark studies. Depending on the qualifications and preferences of the candidate, the work may entail experimental investigations and/or modelling in the open-source computational fluid dynamics
-
in the open-source computational fluid dynamics (CFD) code PDRFOAM. The work will be conducted in collaboration with other research projects on hydrogen safety at the department. The position offers a
-
employment period is three years. A premise for employment is that the PhD Research Fellow will be enrolled in USN's PhD-program in Technology within three months after accession. About the PhD-project