Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
publication record in psycholinguistics, Nordic linguistics, corpus linguistics, sociolinguistics, or related fields Experience with R (data wrangling, visualization, statistical modelling) Experience with
-
aerodynamic) and structural integrity analysis, primarily using numerical methods and surrogate models. The candidate is expected to work collaboratively in an international research environment. The research
-
Interest in experimental work, numerical modelling, and field investigation Experience with data processing and the analysis of material and structural response Experience with field implementation and on
-
engineering applications, with familiarity with strength and durability tests on conventional construction materials Interest in experimental work, numerical modelling, and field investigation Experience with
-
. 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
-
interactions. This involves (i) developing predictive machine learning models that forecast user actions and remote system responses across audio, video and haptic modalities, and (ii) jointly orchestrating
-
institutional structures and priorities. HERITOUR investigates how current collaborations function and how cross-sectoral policies can be developed within a democratic and regenerative governance model
-
collaboration will be positively evaluated, in particular if the candidate has shown an ability to combine experiments with theory/modeling. Good communication skills are a prerequisite. Required qualifications
-
, combining space craft data analysis with opportunities for modelling depending on the candidate’s interests. The successful candidate will have the opportunity to join the science teams of three major Mars
-
. The aim is to develop and analyze advanced models that integrate heterogeneous maritime data sources - such as AIS, metocean, emissions, port, cargo, and business data - to improve predictions of costs