Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Delft University of Technology (TU Delft)
- European Space Agency
- Eindhoven University of Technology (TU/e)
- University of Twente
- Leiden University
- Utrecht University
- Wageningen University & Research
- Eindhoven University of Technology
- Erasmus University Rotterdam
- Radboud University
- University of Amsterdam (UvA)
- Maastricht University (UM)
- Tilburg University
- University of Twente (UT)
- Vrije Universiteit Amsterdam (VU)
- Zuyd University
- 6 more »
- « less
-
Field
-
Is the Job related to staff position within a Research Infrastructure? No Offer Description Computational geometry is the area within algorithms research dealing with the design and analysis
-
a focus. Traditionally, this is done through iterative algorithms (‘trial and error’). In this project, we aim to develop a radically different approach where the correct shape is computed using a 3-D
-
participation of citizens. You will focus on developing adaptive learning systems that enhance the transparency and contestability of AI decisions through personalized, multimodal explanations. Your job AI is
-
(LES) results. Key Responsibilities: Develop and refine numerical algorithms for real-time wind field forecasting. Validate forecasting models against high-fidelity LES data and field measurements
-
and democratic participation of citizens. You will focus on developing adaptive learning systems that enhance the transparency and contestability of AI decisions through personalized, multimodal
-
-house and external scientific studies for mission development and implementation, geophysical algorithm development and related research activities; organising mission-specific science workshops and
-
contests to facilitate the generation, development, and implementation of new products, services, processes, and business model ideas. However, out of a pool of submitted ideas, typically only a few will be
-
remote sensing technology and real-time turbine control. Your focus will be the development of a predictive capability that allows turbines to react to the wind before it hits the blades. Using upstream
-
technological research and development (R&D) concerning turnkey onboard hardware data handling solutions, with an emphasis on: platform and payload data handling architectures and their building blocks (equipment
-
given model. As a second task, you will work on software development for model learning, and in particular, on the Python library AALpy . Model learning is done algorithmically, by sending inputs to and