Sort by
Refine Your Search
-
-informed machine learning) and integrating uncertainty quantification into these workflows. You are familiar with environmental or soil science applications (e.g., carbon, nitrogen, biomass modelling). You
-
-based knowledge with machine learning. You will work closely with the Utrecht University team and OpenGeoHub together with other project partners, to develop and implement surrogate and hybrid modelling
-
partners to reduce CO2 emissions in steel production using machine learning. You can find more information here . You will work on a theoretical and an applied project on data-enhanced physical reduced order
-
Strong quantitative skills and experience with scientometric methods, machine learning for text analysis, and possibly LLMs. Experience with the analysis of science and technology data (patents and
-
. The employment of machine learning techniques for guidance, navigation and control functions for increased autonomy on board with respect to environmental or modelling disturbances or mission-critical phases (also
-
records from satellite data, and/or improved methods of uncertainty characterisation, including the use of artificial intelligence and machine learning to improve or analyse satellite climate data records
-
Model of Immersive Learning (CAMIL) by empirically examining how immersive VR supports learning processes across educational contexts. This position is part of a larger project funded by the Nationaal
-
of a model-based digital twin to be applied to cryogenic liquid propulsion systems and their main components using innovative techniques such as chemical reactor networks or surrogate models for machine
-
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
-
develop a simplified model focusing on the leader stage. You will: Analyze experimental data and microscopic simulations Identify relevant physical features and parameters Apply machine learning techniques