Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- University of Oslo
- University of Bergen
- NTNU - Norwegian University of Science and Technology
- Nature Careers
- UNIS
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- NHH Norwegian School of Economics
- NORCE
- Norwegian Institute of International Affairs
- Norwegian University of Life Sciences (NMBU)
- UiT The Arctic University of Norway
- University of South-Eastern Norway
- 2 more »
- « less
-
Field
-
of Physics and Technology, Mathematics and Statistics, and Computer Science. More about the position We welcome applicants with a strong background in machine learning, causal inference, and statistics, who
-
Bayesian inference, stochastic algorithms and simulation-based inference; and statistical machine learning. OCBE has collaborations with leading biomedical research groups in Norway and internationally. OCBE
-
will be adapted to the candidate’s background and the evolving needs of the center. Possible directions include the application of rock physics models, Bayesian inversion methods, and machine learning
-
physics models, Bayesian inversion methods, and machine learning algorithms in the electromagnetic context. Qualifications and personal qualities: Applicants must hold a master’s degree (or equivalent) in
-
implement a framework to infer anisotropic viscosity from both ice and mantle textures in a numerical flow model. This will open new avenues for understanding solid earth and cryosphere dynamics, and their
-
between ice and mantle dynamics. In DYNAMICE, we will implement a framework to infer anisotropic viscosity from both ice and mantle textures in a numerical flow model. This will open new avenues
-
ethnomycology or ethnobiology large-scale (ethnographic) database construction phylogenetic comparative analyses with Bayesian computational tools The applicant must have the ability to work independently and in
-
analyses, including demographic inference, selection scans, and gene-environment and gene-phenotype association studies. • Plan and conduct fieldwork to collect plant material across Arctic locations, and
-
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
-
, 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