58 computing-"Computer-Vision-Center" "Computer Vision Center" PhD positions in Netherlands
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Are you excited about designing the next generation of energy-efficient AI hardware? Do you want to contribute to cutting-edge research at the intersection of neuromorphic computing, computer
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. The project brings together expertise in artificial intelligence, computer vision, human-computer interaction, and psychology. Its technical core lies in developing robust and adaptive visual speech
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Eindhoven University of Technology (TU/e) | Eindhoven, Provincie Noord-Brabant | Netherlands | 2 months ago
Deadline 4 Oct ’26 Published yesterday Vacancy ID 2026/488 Apply now 52 days remaining Save Get personalised job matches! Create an account in 2 minutes! Research fields Engineering; Computer science Job
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Computer science Job types PhD Education level University graduate Weekly hours 38 hours per week Salary indication €3059—€3881 per month Location De Boelelaan 1111, 1081HV, Amsterdam View on Google
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the Computer Science department, you will work in a vibrant, interdisciplinary community that investigates how computing technologies shape the way we interact with the world and each other
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electrical engineering, computer science or a closely related field. A solid foundation in computer vision, pattern recognition, AI-related techniques. Hands-on interest in designing methods using
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part of your time (up to 10%) on teaching activities, such as assisting in courses of our computing science programmes. Would you like to learn more about what it’s like to pursue a PhD at Radboud
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development vision and the ESA Vision 2040. To this end, the Department has defined strategic roadmaps for key technologies aimed at developing key capabilities in line with the strategic vision. To
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Vacancy ID 2026/499 Apply now 30 days remaining Save Get personalised job matches! Create an account in 2 minutes! Research fields Engineering; Computer science Job types PhD Education level University
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control, visual landing and event-based vision, scientific deep learning for physical systems, spiking neural networks for event-based systems. Building on this experience, the research line on the theory