We are recruiting outstanding Research Interns to work on autonomous vehicles, robotics, and physical AI! Intelligent machines that can perceive, reason, and safely interact with people and the physical world are rapidly becoming a reality. Self-driving cars, autonomous delivery and construction vehicles, mobile manipulators, and other robotic systems are moving closer to widespread deployment. However, fundamental research challenges remain before these systems can operate safely, reliably, and autonomously in complex, unfamiliar environments. For example, how can we: Develop new training paradigms that use perception and interaction to train autonomous vehicle and robot policies in closed loop? Equip autonomous systems with online and offline assurances that meet the requirements of safety-critical applications? Enable vehicles and robots to navigate across new environments, tasks, and embodiments? Build systems that reason under uncertainty and interact safely and naturally with people and other agents? These are some of the exciting questions being explored by NVIDIA’s Autonomous Systems and Physical AI Research (ASPIRE) group. Our diverse, interdisciplinary team conducts foundational research spanning foundation model design, embodied reasoning, safety, closed-loop training and evaluation, and agentic workflows for Physical AI development. We also investigate related areas including decision-making under uncertainty, deep learning, reinforcement learning, simulation, and the verification and validation of safety-critical AI systems. Our focus is on fundamental research, and lab members are encouraged to publish their work and open-source their code. NVIDIA is known for its collaborative culture, and our researchers work closely with experts across the company in autonomous vehicles, robotics, perception, simulation, and machine learning. This creates opportunities to influence real-world products while retaining the freedom and bandwidth to conduct groundbreaking, publishable research.
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Job Type
Full-time
Career Level
Intern
Education Level
Ph.D. or professional degree