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AI and robot learning Vision-language-action (VLA) or multimodal AI modeling Perception, control, or interaction for robotic systems Deep learning or applied machine learning for robotics Practical
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systems capable of understanding, learning, and acting in complex, dynamic settings. The team works at the intersection of computer vision, multimodal learning, and robotics to create next-generation
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environment with strong industrial links and a focus on innovation and sustainability. https://www.tum.de/ Chair of Perception for Intelligent Systems (PercInS) PercInS develops AI-driven perception systems
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. The team works at the intersection of computer vision, multimodal learning, and robotics to create next-generation embodied agents that interact naturally and safely with humans and their environments
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of design, computation, and robotics. ARG's research interests include topics such as robot learning, human-robot interaction, Generative AI, computer vision, closed-loop control, additive manufacturing
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federated learning, AI security and privacy, quantum machine learning (QML), robotics, and/or AI-driven discovery in science and engineering (e.g., genomics, bioinformatics, drug discovery, infectious disease
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equivalent university degree in psychology or a related discipline (computer science, neurosciences, biology, cognitive sciences) • Skills in perception psychology, neurosciences, machine learning, tracking
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researchers within the Neuroscience of Attention Perception Laboratory (NAPL) on non-human primate (NHP) studies investigating neural mechanisms of cognition. The research specialist will work alongside fellow
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PI & HOSTING GROUP The direct responsible persons for this post are Dr. Joost van de Weijer and Bogdan Raducanu, members of the Learning and Machine Perception (LAMP) team at the CVC. For more
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(including ultra-high-field and ultrafast MRI) Computational and network neuroscience Machine learning and biologically inspired AI Vision science and predictive coding Clinical neuroscience and