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experimentation. The PhD student will develop models and algorithms for the joint design of sensing, communication, inference, and action, and is expected to contribute to a real robotic platform integrating
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thermal systems, controls, or AI/ML applications Experience developing and deploying reinforcement learning algorithms for real-time control applications Experience with hardware-in-the-loop (HIL) testing
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pose estimation algorithms. The models and algorithms you develop will be part of open source and data repositories affiliated with the broader research program and TU Delft’s commitment to Open Science
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(AI) and machine learning (ML) methodologies. The position involves annotating clinical data, collaborating with AI/ML/NLP teams, developing algorithms, and generating insights to improve patient care
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sensor fusion frameworks using cameras, LiDAR, depth sensors, and other sensing technologies. Develop object detection, segmentation, tracking, and pose estimation algorithms. Develop navigation
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sensors, and other sensing technologies. Develop object detection, segmentation, tracking, and pose estimation algorithms. Develop navigation, localisation, path planning, and collision avoidance algorithms
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geometrical changes [Nat Commun. 16, 11388]. In this project you will push the boundaries of algorithm based reconstruction of nanoscale strongly scattering geometries from their radiation pattern. We seek
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-inspired, method-driven theory to application-driven research. Join our team as a dedicated scientist and contribute to our exciting research projects. Our work focuses on models and algorithms
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developing representations, using neuroimaging with fMRI and OPM-MEG, and to model the developmental process using computational models from AI. The project aims to better understand infant cognition, develop
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ARIA project Enforcing Safety in Cyber-Physical Systems via Proof Certificates, and focus on the design, development, and application of Safe RL algorithms as well as their verification via Proof