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- Delft University of Technology (TU Delft)
- Delft University of Technology (TU Delft); yesterday published
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- Delft University of Technology (TU Delft); 17 Oct ’25 published
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- University of Amsterdam (UvA); Amsterdam
- Delft University of Technology (TU Delft); today published
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- Eindhoven University of Technology (TU/e); 4 Oct ’25 published
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algorithms) Proficient in English. For information please check the Graduate Schools Admission Requirements. Familiarity or interested in using machine learning is also desiered. TU Delft (Delft University
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. Experience working on inversion problems (e.g., MCMC type algorithms) Proficient in English. For information please check the Graduate Schools Admission Requirements. Familiarity or interested in using machine
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aims to rethink how soft robots can interact with their environment, focusing on large-area, multi-point contacts—similar to how an elephant wraps its trunk around an object. Unlike traditional robots
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trunk around an object. Unlike traditional robots, which rely on rigid links and localized interaction points, soft robots are composed of deformable materials that can conform to complex geometries and
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3 Sep 2025 Job Information Organisation/Company University of Amsterdam (UvA) Research Field Computer science » Informatics Computer science » Programming Mathematics » Algorithms Mathematics
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11 PhD positions at several universities, focusing on different aspects of positive energy districts. The project also involves a large range of project partners, e.g. municipalities, building
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new generation of perceptual foundation models by contributing advanced perceptual pre-training and fine-tuning algorithms. What you will do You will carry out research and development in the areas
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-tuning algorithms. What you will do You will carry out research and development in the areas of perceptual foundation models, using advances in deep machine learning and computer vision. The goal is to
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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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scales and different phases which leads to nonlinear time and history dependent material behavior. Additionally, innovative changes are happening in the steel production process, especially in the drive