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- Delft University of Technology (TU Delft)
- European Space Agency
- Delft University of Technology (TU Delft); 16 Oct ’25 published
- Delft University of Technology (TU Delft); today published
- Delft University of Technology (TU Delft); yesterday published
- Tilburg University
- Tilburg University; 16 Oct ’25 published
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Field
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Location ESRIN, Frascati, Italy Description Data Quality and Cal/Val Manager for Atmospheric Sensor Missions in the Sensor Performance, Products and Algorithms Section, Earth Observation Mission
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: The use of data science and AI methods and techniques within the security and cyber domain, with special focus on ethics and algorithmic transparency; Human-Technology Interaction: Developing robots
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Do you have significant experience with algorithms for interval path planning, and are you motivated to bring these closer to the railway industry? Then this position is for you! Job description The
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the security and cyber domain, with special focus on ethics and algorithmic transparency; Human-Technology Interaction: Developing robots, simulations, and games, which use a variety of AI technologies to learn
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Description Do you have significant experience with algorithms for interval path planning, and are you motivated to bring these closer to the railway industry? Then this position is for you! Job description The
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, specialized compilers, and robust algorithms and implementations, in addition to the creation of dedicated design tools and methodologies. The Computer Engineering (CE) section of the Department of Quantum
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stability of swarm behaviour, and validate novel control strategies that quickly adapt to rapid changes in supply/demand. New effective market, contracting, and algorithmic mechanisms are needed to be derived
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, prove the convergence and stability of swarm behaviour, and validate novel control strategies that quickly adapt to rapid changes in supply/demand. New effective market, contracting, and algorithmic
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from multispectral datasets You will contribute to the ongoing development of Machine Learning algorithms for recognition of planetary materials from multispectral datasets. This project combines deep