Human Interactive Driving Intern – World Models

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
 
You’ll be joining a multidisciplinary research team focused on developing a world foundation model for driving—a unified, transferable representation of driving knowledge built from large-scale real-world and simulated data.  Together, we are tackling the complex challenges of multi-agent interaction, causal reasoning, and embodied intelligence in highly dynamic, real-world driving environments. Our approach is inspired by cutting-edge generative modeling techniques and powered by scalable infrastructure and open-source data, and we work closely with engineers to deploy our models in simulation and on hardware.
 
The Internship
 
As a Ph.D. Research Intern, you will conduct original research at the intersection of machine learning and autonomous driving. Your work may focus on developing novel components of world models, improving decision-making through model-based RL, advancing 3D perception for dynamic scenes, or enhancing simulation-to-reality transfer. You’ll have the opportunity to prototype and evaluate your ideas in closed-loop simulations and contribute to research publications alongside TRI scientists. This is an opportunity to test and refine your research in a collaborative, high-impact environment, while working with real-world data and contributing to the future of autonomous systems.  The internship will be in our headquarters and include competitive compensation, befitting the challenging but fun nature of the research work at TRI. Applicants with relevant publications in the fields above and good collaboration skills are highly encouraged to apply.