Politecnico di Torino invites applications for a research fellowship in video understanding for robotic applications. It addresses learning action-level representations from videos to instruct humanoid robots in long-horizon manipulation tasks.
The project will develop hierarchical, affordance-aware, and goal-conditioned representations feeding motor policies based on reinforcement and imitation learning, with emphasis on large-scale video understanding for human behavior analysis.
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📌 Robotics Engineer: Master Low-Level Manipulations from Demos (Roma)
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