Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- University of Oslo
- NTNU - Norwegian University of Science and Technology
- University of Bergen
- UiT The Arctic University of Norway
- NTNU Norwegian University of Science and Technology
- Nord University
- Simula Research Laboratory
- The Norwegian Polar Institute
- BI Norwegian Business School
- NHH Norwegian School of Economics
- Norwegian Meteorological Institute
- Norwegian University of Life Sciences (NMBU)
- University of Agder
- 3 more »
- « less
-
Field
-
consisting of both control theory (or related fields) and economics (or related fields). Applicants must have experience in one or more of the topics: Model-predictive control Numerical optimization
-
archaeological excavations and dating with climate modelling on the one hand and research on human minds and sociality on the other. The PhD position will be part of an interdisciplinary project with the goal
-
, utilisation of natural resources, shipping, predictive modelling, or climate risk Core courses in probability and statistical inference, optimisation, microeconomics, scientific methods Elective courses in
-
) in bioinformatics, computational biology, data science, or related fieldsForeign completed degrees (M.Sc.-level) must correspond to a minimum of four years in the Norwegian educational system
-
nuclear structure models, and to understand how elements heavier than iron are formed in explosive stellar environments. The current project is closely related to the research activity “Nuclear Properties
-
-cycle fatigue. The research methods are based on both small-scale and full-scale experimental testing and on Finite Element Modelling. Are you motivated to take a step towards a doctorate and open
-
. Required: Master’s degree (or equivalent) in bioinformatics, computational biology, data science, or related fieldsForeign completed degrees (M.Sc.-level) must correspond to a minimum of four years in
-
and develop frameworks and knowledge on planning and coordination of resources within and across projects. apply quantitative methodologies, such as simulation and analytical modelling, to develop