Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Oslo
- University of Bergen
- University of South-Eastern Norway
- UiT The Arctic University of Norway
- NTNU - Norwegian University of Science and Technology
- University of Stavanger
- University of Agder
- University of Inland Norway
- Western Norway University of Applied Sciences
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- Nature Careers
- Norwegian University of Life Sciences (NMBU)
- OsloMet
- 3 more »
- « less
-
Field
-
flow law, compare it to similar research on olivine, and help implementing this model into the geodynamic software ASPECT. The aim is to develop a single method for anisotropic flow modelling for both
-
or more of the following empirical research methods will be considered an advantage: applied microeconometrics and causal inference; machine learning and data science. Experience with one or more of the
-
from educational philosophy, cultural psychology and humanities studies in special education and health. Through analytical-hermeneutic methods, the project will explore frameworks of understanding and
-
doctoral degree in digital culture, digital humanities, computational media, or a related field, including computer science if the dissertation project had a significant humanistic component. The doctoral
-
dissecting the functionality of different EV subsets. Methods include, but are not limited to, in vitro culture of primary human cells and cell lines, organ-on-chip models, molecular biology, diverse
-
increasingly recognized as a key factor in understanding climate variability and have the potential to improve seasonal to decadal climate predictions. The PhD candidate will investigate mechanisms of such basin
-
communication skills in English (see below) Additional desired qualifications: Experience with the theoretical description of transport processes Skills in advanced computational methods (e.g., C++) Jarli og
-
, school-level aggregated data, and genetic data. The successful candidate is expected to use state-of-the-art research methods for drawing causal inferences from non-experimental data. The successful
-
practical insights for a fair and resilient tourism industry. The project will employ a combination of qualitative and quantitative research methods. It can draw on various theoretical perspectives, with
-
accurate representation of available transmission capacity, thereby reducing congestion and improving the integration of renewable energy sources. This method enhances market efficiency by optimizing spatial