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- Delft University of Technology (TU Delft)
- Delft University of Technology (TU Delft); 3 Oct ’25 published
- Delft University of Technology (TU Delft); yesterday published
- Eindhoven University of Technology (TU/e)
- Eindhoven University of Technology (TU/e); Published yesterday
- Universiteit van Amsterdam
- University of Amsterdam (UvA)
- University of Amsterdam (UvA); yesterday published
- Wageningen University & Research
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Field
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Do you want to be part of an industry-oriented project and work on flexibility estimation from industrial sites? The envisioned research is part of the research program Intelligent Energy Systems
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and work on flexibility estimation from industrial sites? The envisioned research is part of the research program Intelligent Energy Systems (IES) performed within the Electrical Energy Systems (EES
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movements during art (exhibitions) experiences and relate those to parameters of lighting design and perception. This project will be supervised by Maarten Wijntjes and Sylvia Pont. PhD candidate / project 13
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discovery, and computational design. Extending our existing theoretical frameworks in investigating design optimization and nonlinear parameter estimation. Contributing to the teaching and assisting with
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. Extending our existing theoretical frameworks in investigating design optimization and nonlinear parameter estimation. Contributing to the teaching and assisting with dynamics relevant courses
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parameters that have been learned from data. For instance, why does a machine learning model predict that it is unsafe to discharge a certain patient from the intensive care? Or which characteristics make a
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incomprehensible model parameters that have been learned from data. For instance, why does a machine learning model predict that it is unsafe to discharge a certain patient from the intensive care? Or which
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have control over our spatiotemporal sampling of observational data locations, we first define the population. Next, we sample population units for (1) design-based estimation of population parameters
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exploratory eye and body movements during art (exhibitions) experiences and relate those to parameters of lighting design and perception. This project will be supervised by Maarten Wijntjes and Sylvia Pont. PhD
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learning models keep getting better, but how they make their decisions often remains unclear, because these depend on many incomprehensible model parameters that have been learned from data. For instance