Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Oslo
- University of Bergen
- UiT The Arctic University of Norway
- University of South-Eastern Norway
- University of Stavanger
- NTNU - Norwegian University of Science and Technology
- University of Agder
- ;
- University of Inland Norway
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- Nature Careers
- Nord University
- Norwegian University of Life Sciences (NMBU)
- OsloMet
- The Norwegian Polar Institute
- Western Norway University of Applied Sciences
- 6 more »
- « less
-
Field
-
something we aim to achieve in the project. The work will involve theoretical and computational modelling of the droplets and how they wet soft interphases. It is planned that the numerical simulations and
-
advanced computational methods. Knowledge of c++ program-ming language is particularly desirable Experience with supervising Bachelor/Master/PhD students Strong track record relative to the career stage
-
years. The nominal length of the PhD programme is three years. The fourth year is distributed as 25 % each year and will consist of teaching and other duties. The objective of the position is to complete
-
to the level of a doctoral degree. Admission to the PhD programme is a prerequisite for employment, and the programme period starts on commencement of the position. The PhD fellow position is for a period of
-
oppdatert 02.08.2025 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 skadelige programmer eller
-
Cookie-erklæringen var sist oppdatert 14.06.2025 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
-
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
-
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
-
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
-
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