Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
to the ground segment and operations domains, for the procurement and delivery of data systems in support of ESA’s Space Safety Programme, and as a matrix support provider to ESA programmes and mission operations
-
Apply now We are offering a full-time, three-year Postdoc position as part of the Dutch Research Council external link (NWO) ENW-XL programme. You will join the Levato research group at the Regenerative
-
alignment with the strategic directions of the STS PNRR programme. Scientifically, you will in particular: propose and conduct rigorous research in the field of model-based digital system engineering and
-
in combination with other machine learning techniques, to create predictive models. You will engage in an interactive feedback loop with domain experts to analyze discovered models and remove any
-
to reduce these emissions by at least 1 Mton in 2030. In support of these policies, several research projects funded at (sub-, inter-) national level (such as the Netherlands Research Programme on Greenhouse
-
learning with a background in robust and embedded control, aerospace systems and physical modelling, as well as in artificial intelligence-related concepts, computer vision and numerical optimisation
-
to keep the data up-to data with very little effort. Estimate energy and land needs for the realization of the CCU potential. Develop a multi-objective optimization model for individual CCUS projects
-
sensing provides large-scale and consistent observations, in-situ data collection remains a vital component for ground-truthing, model calibration, and validation of automated monitoring. However
-
candidate would become an ARIA R&D creator. Responsibilities: Conduct foundational research on aggregation mechanisms, including: for-mal modeling and axiomatic analysis, computational complexity and algo
-
(e.g. Presentation, PsychoPy, E-Prime, Gorilla). You have experience in data analysis, visualisations and programming in R and/or Python. You have experience with statistical models (e.g. mixed-effects