PhD Research Intern, Autonomous Systems and Physical AI Research
Job Description
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
What You'll Be Doing
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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
What You'll Be Doing
- Designing and implementing cutting-edge techniques for autonomous vehicles, robotics, and physical AI.
- Conducting original research and publishing your results.
- Collaborating with research colleagues, internal product teams, and external researchers.
- Transferring technology you've developed to relevant product groups.
- Currently pursuing a PhD in Robotics, Computer Science, Computer Engineering, or a related field.
- Relevant research experience in autonomous vehicles, robotics, embodied AI, or autonomous systems.
- Strong knowledge of the theory and practice of vehicle or robot autonomy—or expertise in a related area, with a strong interest in applying your work to autonomous systems.
- A track record of research excellence, demonstrated through publications at leading conferences and journals—such as RSS, ICRA, CoRL, IJRR, NeurIPS, ICML, CVPR, TAC, etc.—and through other research artifacts such as open-source software.
- Exceptional Python programming skills; experience with C++ and parallel programming, such as CUDA, is a plus.
- Experience with machine learning frameworks such as PyTorch.
- Strong communication and interpersonal skills are required, along with the ability to thrive in a dynamic, research-focused team.
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More Info
Key Skills
machine learning frameworks
verification and validation of safety-critical AI systems
