PhD Research Intern, Learning Embodied Skills from Human Data - 2027

Responsibilities

• Innovate and implement novel AI algorithms that transform large-scale human data into controllable motion and interaction skills across physical and digital embodiments.
• Develop robust, scalable training and inference pipelines for motion reconstruction, generation, retargeting, and character and robot control.
• Build methods that transfer human skills to humanoid robots, including whole-body loco-manipulation and dexterous manipulation.
• Maintain a close, collaborative relationship with your mentor(s).
• Publish your research findings at leading computer vision, machine learning, graphics, and robotics conferences.
• Partner with product teams to enable effective technology transfer of your work.
• Research Topics Include
• Human motion and human-object interaction reconstruction, synthesis, and generation.
• Learning character and robot skills from video, motion-capture, and teleoperation data.
• Cross-embodiment motion generation, retargeting, and tracking.

Languages