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

Details

NVIDIA is seeking outstanding Research Interns to join the Data-Driven AI for Robotics (DAIR) group. The focus is on learning embodied skills from large-scale human data. The objective is to develop AI systems that capture, understand, and reproduce complex human motion and interaction skills across physical and digital embodiments, including humanoid robots and animated characters.

The research spans the full stack: reconstructing human motion and human-object interactions from video; generating diverse, controllable character behaviors; transferring motion across embodiments; and training physically grounded controllers for humanoid robots and interactive virtual characters.

Interns will collaborate with a research team that produces work published at leading computer vision, machine learning, graphics, and robotics conferences. The role also provides opportunities to collaborate with research and product teams across NVIDIA.

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 mentors.
• Publish research findings at leading computer vision, machine learning, graphics, and robotics conferences.
• Partner with product teams to enable effective technology transfer.

Research Topics

• 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.
• Whole-body humanoid control, loco-manipulation, and dexterous manipulation.
• Reinforcement learning and imitation learning.
• Differentiable physics simulation and physically grounded motion generation.
• World action models, vision-language-action models, video and motion foundation models, and LLM-based agents for data generation and embodied AI.

Requirements

• Pursuing a PhD degree in Computer Science, Computer Engineering, Electrical Engineering, Robotics, or a related field.
• Highly efficient and creative use of coding agents to accelerate research prototyping, experimentation, and development.
• Outstanding engineering skills in rapid prototyping and developing model-training and simulation frameworks such as PyTorch, Isaac Lab, and MuJoCo.
• Excellent skills working with large-scale machine learning and AI systems and compute infrastructure.
• A promising research track record with at least one publication at a leading computer vision, computer graphics, or robotics conference, such as CVPR, ICCV, SIGGRAPH, or CoRL.
• Preferred experience includes 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.

Compensation and Benefits

• Internship hourly rate: 38 USD–94 USD, based on position, location, year in school, degree, and experience.
• Eligibility for NVIDIA intern benefits.

Applications will be accepted at least until September 25, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.