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

What you'll do

• Develop AI algorithms and scalable pipelines for motion reconstruction, generation, retargeting, and control.
• Build methods for transferring human skills to humanoid robots, including whole-body loco-manipulation and dexterous manipulation.
• Publish research and collaborate with mentors and product teams on technology transfer.

What they ask for

• Currently pursuing a PhD in Computer Science, Computer Engineering, Electrical Engineering, Robotics, or a related field.
• Highly efficient and creative use of coding agents for research prototyping, experimentation, and development.
• Strong engineering skills in rapid prototyping and model-training and simulation frameworks.
• Excellent skills working with large-scale machine learning/AI systems and compute infrastructure; at least one publication at a leading computer vision, graphics, or robotics conference.

Nice to have

• Experience in human motion modeling, human-object interaction, character animation, robot learning, reinforcement or imitation learning, cross-embodiment motion tracking, generative modeling, video understanding, or differentiable physics simulation.

Pay

38 USD - 94 USD per hour; internship hourly rate

Tools

PyTorch, Isaac Lab, MuJoCo

AI focus

Research and develop embodied AI for learning, reconstructing, generating, and transferring motion and interaction skills from human data to robots and digital characters; work may involve reinforcement and imitation learning, foundation models, and LLM-based agents.