Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Oslo
- University of Bergen
- UiT The Arctic University of Norway
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
- University of Agder
- University of South-Eastern Norway
- University of Stavanger
- Western Norway University of Applied Sciences
-
Field
-
. The objective is to further develop and validate machine-learning surrogate models derived from high-fidelity multiphysics simulations of reactor transients and quantify how surrogate uncertainties propagate
-
many areas of applied and theoretical statistics and data science, and is heavily involved in research at the crossing of statistics and machine learning. The focus of this postdoctoral fellowship is to
-
strategic career path, all PhD fellows are expected to submit a career development plan, specifying career goals and the competencies that the PhD fellow should acquire, no later than one month after
-
fellow will be part of a growing team of researchers, postdocs and PhD students working on intelligent observing systems using machine learning and data assimilation methods in the ACTIVATE project. UiO
-
of statistics and machine learning. Modern vessels produce vast amounts of multivariate data streams. The project addresses the development of trustworthy statistical and machine learning methods for anomaly
-
effectively exploited, possibly using some kind of machine learning algorithm, provides more accurate data than traditional data collection methods, e.g. paper-based surveys. This data is valuable to several
-
with programming in Python is a requirement Experience with telecentric particle imagers, image analysis, and machine learning for particle recognition is an advantage Experience of working with wave
-
requirement Experience with telecentric particle imagers, image analysis, and machine learning for particle recognition is an advantage Experience of working with wave flumes to study entrainment is an
-
should acquire, no later than one month after commencement of the fellowship period. The department is responsible for ensuring that the plan is followed up and that the PhD fellow has access to career
-
and Distributed Systems Research Group (ND) with co-supervision from IFI’s Machine Learning section and the University of Inland Norway’s research group for User Perception and Engagement in XR