Robotics Simulation and Evaluation PhD Intern - Summer 2027

Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in an inclusive, encouraging environment where everyone is inspired to do their best work. Come join the team and see how we can make a lasting impact on the world.
We are looking for dedicated interns to join our robotics team. You will develop novel approaches to agentic robot policies, world action models, robot policy training and evaluation, and sim-to-real transfer, working alongside the researchers and engineers who build NVIDIA's robotics and simulation platforms. Our internships are an excellent opportunity to grow as a researcher and gain hands-on experience with industry-leading robotics teams. We are looking for curious, ambitious, and collaborative individuals who take ownership of open-ended problems and are excited to help us tackle challenges no one else can solve.
What you'll be doing
Work closely with experts in robotics and machine learning to scope a ch project that is both scientifically novel and relevant to NVIDIA's robotics roadmap.
Design, implement, and evaluate new robot learning methods using GPU-accelerated simulation and, where appropriate, real robot hardware.
Run rigorous experiments: build strong baselines, design evaluation protocols, ablate your ideas, and communicate clearly.
Write clean, well-documented research code that other team members can build on.
Collaborate with researchers and internal product teams to transfer your research into NVIDIA products and platforms.
Deliver results as prototypes, patents, product contributions, and publications at top-tier venues.
What we need to see
Currently enrolled in a Ph.D. program in Computer Science, Electrical Engineering, Robotics, or a related field.
Research experience in one or more of the following: agentic policies, world action models, robot policy training and evaluation, or sim-to-real transfer, demonstrated through publications, preprints, a thesis, or open-source projects.
Strong Python skills and hands-on development experience with a modern deep learning framework (e.g., PyTorch, JAX).
Strong written and verbal communication skills, including presenting research results to both experts and non-experts.
Ways to stand out from the crowd
First-author publications at top robotics and machine learning venues (e.g., CoRL, RSS, ICRA, IROS, NeurIPS, ICML, ICLR, CVPR).
Deep expertise in robot learning: reinforcement learning, imitation learning, or training and fine-tuning large vision-language-action (VLA) or world models for robotics.
Deep expertise in GPU-accelerated physics simulation (e.g., PhysX, Isaac Gym / Isaac Lab, Newton, MJX), including building simulation environments, assets, or domain randomization pipelines.
Experience deploying learned policies on real robot hardware (manipulators, humanoids, or mobile robots) and closing the sim-to-real gap.
Experience with large-scale, multi-GPU training and data pipelines with contributions to open-source robotics or simulation projects.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!