Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- University of Oslo
- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
- Norwegian University of Life Sciences (NMBU)
- University of Bergen
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- Nord University
- Molde University College
- NORCE Norwegian Research Centre
- Simula UiB
- University of Agder
- University of Stavanger
- 2 more »
- « less
-
Field
-
16th March 2026 Languages English English English The Department of Structural Engineering has two vacancies for SFI FAST: PhD positions in Modelling Strength and Failure in Recycled Aluminium
-
topics include (a) AI, machine learning, and large language models for measurement challenges (e.g., for small-sample calibration or for accelerated algorithms), (b) identifying and investigating aberrant
-
candidates within Modelling Strength and Failure in Recycled AluminiumAlloys funded through the Centre for Research-based Innovation SFI FAST – Future Aluminium Structures. The positions are linked
-
PhD Research Fellow in Theoretical and Computational Active Matter Physics for Glioblastoma Invasion
, computation, and experiments to model and manipulate the physical forces experienced by invading cancer cells. The overarching goal is to identify biomechanical “weak points” in cancer cell invasion and to
-
candidate will conduct advanced methodological and psychometric research. Potential topics include (a) AI, machine learning, and large language models for measurement challenges (e.g., for small-sample
-
exhibit hallmarks of active matter. This PhD project aims to develop theoretical and computational active-matter models of early mouse embryogenesis that couple collective cell mechanics with gene
-
models to identify habitable planets around other stars. Within three different research themes: (1) Planets and Early Earth, (2) Modern Earth, and (3) Exo-Earths, we are keen to explore the internal and
-
PhD Research Fellow in Theoretical and Computational Active Matter Physics for Glioblastoma Invasion
consortium and work closely with three other PhD students, combining theory, computation, and experiments to model and manipulate the physical forces experienced by invading cancer cells. The overarching goal
-
neutron scattering (SAXS/SANS) along with theoretical model analysis including the use of multi-scale and artificial intelligence models. The PD will work closely with both the PhD candidates and PIs within
-
insights into pathogen epidemiology and model parameters. Experience in working with uncertain and historical data. All candidates and projects will have to undergo a check versus national export, sanctions