PhD Research Intern, Robotics and/or Autonomous Vehicles - 2025

By submitting your resume, you’re expressing interest in one of our 2025 Robotics & AV Research focused Internships. We’ll review resumes on an ongoing basis, and a recruiter may reach out if your experience fits one of our many internship opportunities. 

Intelligent machines powered by Artificial Intelligence that can learn, reason, and interact with people are no longer science fiction. An AI-powered robot can build 3D maps of its environment, detect and track real-life objects, learn from simulated environments, and understand language commands. This is truly an extraordinary time — the era of AI has begun. NVIDIA Research has several teams looking for world-class Research Interns including, but not limited to, the Robotics Research Lab in Seattle, Washington, and Santa Clara, California, the Generalist Embodied Agent Research (GEAR) group, and the Autonomous Vehicles Research Group. 

The Robotics Research Lab is passionate about enabling robots to reach human-level dexterity, perception, and adaptability. We are a diverse and interdisciplinary team to work on core robotics topics ranging from control and perception to task planning and critical areas related to Sim2Real and large vision-language-action models. Our interns have the opportunity to publish original research. 

The GEAR group collaborative research team that consistently produces influential works on multimodal foundation models, large-scale robot learning, game AI, and physical simulation. Our past projects include Eureka, VIMA, Voyager, MineDojo, MimicPlay, Prismer, and more. One of our team’s most recent milestones includes Project GR00T, a foundation model for humanoid robots. Your contributions will have a significant impact on our moonshot research projects and product roadmaps. 

The Autonomous Vehicle Research Group brings together a diverse and interdisciplinary set of researchers to address core topics in vehicle autonomy ranging from perception, prediction, planning and control, to long-tail generalization and robustness, as well as advance the state-of-the-art in a number of critical related fields such as foundation models, self-supervised learning, scenario generation and simulation, decision making under uncertainty, and the verification and validation of safety-critical AI systems. 

What you will be doing: 

• Work with experts in robotics and learning to define your research project. 

• Design and implement advanced techniques for robot perception, planning, and control, as well as new AI models for humanoid robots, autonomous vehicles, and embodied agents.