PhD Research Intern, Learning Embodied Skills from Human Data - 2027
Core
Develop AI systems to capture, understand, and reproduce complex human motion and interaction skills across physical and digital embodiments, including humanoid robots and animated characters.
Role type
PhD Research Intern, Learning Embodied Skills from Human Data
Builds
AI systems for motion reconstruction, generation, retargeting, and robot control
Domain
Robotics, Computer Vision, Machine Learning, Graphics
Deliverable
production ML models
Required skills
PhD in CS/Engineering/Robotics, rapid prototyping, model-training frameworks (PyTorch, Isaac Lab, MuJoCo), large-scale ML systems, compute infrastructure, research publication record
Preferred skills
human motion modeling, human-object interaction, character animation, robot learning, reinforcement/imitation learning, cross-embodiment motion tracking, generative modeling, video understanding, differentiable physics simulation
Technologies
PyTorch, Isaac Lab, MuJoCo
Responsibilities
Innovate and implement novel AI algorithms for motion and interaction skills; Develop robust training and inference pipelines; Build methods to transfer human skills to humanoid robots; Publish research findings at leading conferences; Partner with product teams for technology transfer
Seniority
PhD Research Intern
