Robotics Intern, Trustworthy Learning under Uncertainty

At Toyota Research Institute (TRI), we’re on a mission to improve the quality of human life. We’re developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we’ve built a world-class team advancing the state of the art in AI, robotics, driving, and material sciences.
This is a paid 12-week internship opportunity and is a hybrid, in-office role.
Here’s a glimpse into the Internship experience from some of our TRI interns!
The Team
Our Trustworthy Learning under Uncertainty (TLU) team in the Robotics division is looking for Research Interns for Summer 2027 in a variety of areas such as Policy Evaluation, Failure Detection and Mitigation, as well as (Inter)Active and Continual Learning in the context of World Foundation Models (WFM) for Robot Manipulation. Our topics of interest include but are not limited to: Multi-Modal Foundation Models, Generative Modeling, Imitation Learning, Reinforcement Learning, Planning & Control, Statistics, Uncertainty Estimation, Out-of-Distribution Detection, Safety-Aware & Robust ML, (Inter)Active Learning, and Online / Continual Learning. We are aiming to make progress on some of the hardest scientific challenges around the safe and effective usage and development of machine learning algorithms within Robotics. To this end, the research mission of the TLU team is to enable the robust and reliable deployment of embodied foundation models at scale in human environments, while allowing for efficient adaptation to novel settings.
The Internship
As a Research Intern, you will work with a multidisciplinary team proposing, conducting, and transferring pioneering research in Machine Learning for Robot Manipulation. You will use large amounts of sensory data and simulation to solve open problems, work towards publications at top academic venues, and test your ideas in the real world, including on our robots, of course!

Employment type
Intern

Work arrangement
Hybrid