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
- University of Stavanger
- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
- University of Agder
- Western Norway University of Applied Sciences
-
Field
-
algorithms in the electromagnetic context. Qualifications and personal qualities: Applicants must hold a master’s degree (or equivalent) in geophysics or a closely related field such as applied mathematics
-
PhD degree within a period of 3 years. The deadline for applying for admission to the PhD programme at The Faculty of Mathematics and Natural Sciences is 2 months after you start your position or after
-
geophysics or a closely related field such as applied mathematics or theoretical/computational physics. Master’s students may apply if they expect to complete their final examination by 01.10.2025. Employment
-
mobiltelefonen din. En cookie er ikke et program som kan inneholde skadelige programmer eller virus. Hvordan nettsiden bruker cookies Cookies er nødvendig for å få nettsiden til å fungere. Cookies hjelper oss å få
-
learning experts across Integreat research themes. More about the position Machine learning is the mathematical and computational engine of Artificial Intelligence (AI). It is a fundamental force of
-
represented include: fluid mechanics, biomechanics, statistics and data science, computational mathematics, combinatorics, partial differential equations, stochastics and risk, algebra, geometry, topology
-
computer science or statistics A solid background in mathematics, linear algebra and statistics. Documented experience with Bayesian spatiotemporal modelling, including experience with the INLA framework
-
, UiO) and one in Tromsø (UiT The Arctic University of Norway). Machine learning is the mathematical and computational engine of Artificial Intelligence (AI), and therefore it is a fundamental force of
-
personal qualities: Applicants must hold a master's degree or equivalent education in reservoir physics, applied mathematics, chemical engineering, geoscience, applied petroleum technology, or a related
-
-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