The postdoctoral researcher will work on robot learning for manipulation, exploring state-of-the-art Vision–Language–Action (VLA) models for tabletop, mobile, or dexterous manipulation. A key focus is leveraging whole-body motion and/or dexterous, multi-fingered hands to improve perception and control, enabling robots to solve complex, contact-rich tasks that require coordinated base, arm, and hand behaviors in dynamic environments. We seek candidates with a strong background in robotics and machine learning, and demonstrated experience in at least two of the following areas: deep learning, reinforcement learning, imitation learning, robot perception, navigation, grasping, and dexterous or mobile manipulation. Experience in any of the following is especially valued: whole-body control, humanoid or multi-DOF platforms, multi-fingered hands, tactile sensing, or learning-based manipulation in simulation and/or on real systems.
Requirements:
Preferred qualifications:
Great emphasis will be placed on personal skills.
Tagged as: Engineering, Physics
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