PhD Research Intern, Robotics - Summer 2027

Responsibilities

• NVIDIA is at the forefront of the AI and robotics revolution, and NVIDIA’s robotics teams are on a mission to build the essential technology that can enable any company to become a robotics company. The Seattle Robotics Lab is uniquely positioned at the intersection of open academic research and real-world industry impact, pursuing fundamental and applied robotics research across the full robotics stack, including perception, planning, control, reinforcement learning, imitation learning, simulation, and robotics foundation models. This research aims to transform research paradigms, transfer into NVIDIA’s robotics and simulation products, and create new robotics markets for the world.
• We are looking for PhD-candidate interns to play a pivotal role in our research efforts, providing deep, hands-on technical contributions. Our interns must have exceptional research and engineering skills, a strong research track record, and a team-first mindset. You will have the opportunity to achieve real impact, while working with some of the most creative, brilliant, and motivated researchers in the world. Interns can either be working on their own projects typically aligned with one of our internal efforts, or in some cases directly contribute to one of our efforts. Our former interns have gone on to become full-time researchers and engineers at NVIDIA and other world-leading tech companies, started academic careers at top universities, and launched frontier robotics and AI companies.
• Developing algorithms, foundation models, and methods for robotic manipulation and/or loco-manipulation, for industrial, scientific, and household applications;
• Developing AI agents to accelerate research and engineering while ensuring correctness, reproducibility, and security.
• Comfort in working through the complexities of simulation and real-world robotics, including debugging physics simulators and renderers under rapid development; selecting, setting up, maintaining, and enhancing complex robotics hardware; debugging communication systems; and designing robust workflows for model training and evaluation.
• High-precision manipulation and reliable policy deployment

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