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About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
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PhD Research Intern, Learning Embodied Skills from Human Data - 2027 will join the Data-Driven AI for Robotics group to develop AI systems that capture and reproduce complex human motion and interaction skills across physical and digital embodiments. The role involves implementing novel algorithms to transform large-scale human data into controllable motions, building robust training and inference pipelines for reconstruction, generation, retargeting, and robot control. You will work on topics including humanoid loco-manipulation, dexterous manipulation, reinforcement learning, imitation learning, differentiable physics simulation, and vision-language-action models. The position requires expertise in PyTorch, Isaac Lab, and MuJoCo, along with skills in large-scale machine learning systems and compute infrastructure. This research focuses on the technical challenge of transferring human skills to humanoid robots and animated characters using video, motion-capture, and teleoperation data for embodied AI applications.
Implement novel AI algorithms to transform large-scale human data into controllable motion and interaction skills.
Develop robust training and inference pipelines for motion reconstruction, generation, retargeting, and robot control.
Create methods to transfer human skills to humanoid robots for whole-body loco-manipulation and dexterous manipulation.
Research and develop models for human motion and object interaction from video, motion capture, and teleoperation data.
Develop physically grounded motion using reinforcement learning, imitation learning, and differentiable physics simulation.
Build vision-language-action models and LLM-based agents for data generation and embodied AI applications.
Publish research findings at leading computer vision, machine learning, graphics, and robotics conferences.
Partner with product teams to facilitate the successful transfer of research technology into products.
What we're looking for
Pursuing a PhD degree in Computer Science, Computer Engineering, Electrical Engineering, Robotics, or a related field.
Outstanding engineering skills in rapid prototyping and developing model-training and simulation frameworks like PyTorch, Isaac Lab, or MuJoCo.
Excellent skills in working with large-scale machine learning/AI systems and compute infrastructure.
Highly efficient and creative use of coding agents to accelerate research prototyping, experimentation, and development.
A promising research track record with at least one publication at leading computer vision, computer graphics, or robotics conferences.
Experience in human motion modeling, character animation, robot learning, reinforcement/imitation learning, or differentiable physics simulation (preferred).
Experience in cross-embodiment motion tracking, generative modeling, video understanding, or world action models (preferred).
PyTorch
Jax
TensorFlow
Python
C++
CUDA
LLMs
Vision-Language Models
Diffusion Models
Reinforcement Learning
Imitation Learning
Robot Kinematics
Mujoco
Isaac Suite
PID
MPC
Whole Body Control
Python
C++
CUDA
PyTorch
JAX
ROS2
Isaac Sim
MuJoCo
Warp
Reinforcement Learning
Imitation Learning
Sim-to-Real
Computer Vision
Robotics Foundation Models
Model Training
Simulation
Machine Learning
Python
C++
CUDA
PyTorch
Deep Learning
Reinforcement Learning
Robotics
Autonomous Vehicles
Simulation
Machine Learning
Parallel Programming
Closed-loop Training
Verification and Validation
Generative AI
Machine Learning
Computer Vision
NLP
PyTorch
Python
C++
CUDA
Parallel Programming
Multimodal Data
Deep Learning
Research
Rapid Prototyping
CUDA
Python
C++
High-Performance Computing
Parallel Programming
Network Protocols
Computer Architecture
AI Training
Inference
Microarchitecture
Silicon Photonics
Optical Switching
System Design
Routing
Simulation