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- Delft University of Technology (TU Delft)
- European Space Agency
- Delft University of Technology (TU Delft); yesterday published
- Delft University of Technology (TU Delft); Delft
- Delft University of Technology (TU Delft); 17 Oct ’25 published
- Delft University of Technology (TU Delft); today published
- Delft University of Technology (TU Delft); 16 Oct ’25 published
- Tilburg University
- Tilburg University; 16 Oct ’25 published
- University of Groningen
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Field
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, encryption/decryption and compression; use of microelectronics devices (including COTS); implementation, inference, verification and validation of algorithms** on processing hardware platforms for space
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optimization algorithms, you will design structures that deliberately harness modal couplings to exhibit tailored nonlinear behaviour, with direct applications in ultrasensitive resonant sensing. Together
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the second direction, you will explore the geometric design of nonlinear systems. Using nonlinear reduced order modelling (ROM) integrated with optimization algorithms, you will design structures
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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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specialist collaborator to guarantee adequate integration of perception and action; advanced motion-planning and control algorithms, continuously refined via robotic digital twins, enable reliable handling
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for ground/space segment threat collection via existing and novel interfaces, including multi-source sensor intelligence collection, fusion and dissemination. 5) Applied forensics for space missions
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profile, experience and research proposal. Planning and autonomy: The objective is to study the state of the art of planning algorithms that would support onboard autonomous operations of a rover system on
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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