Human Interactive Driving Intern – World Models
About The Position
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 in Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavioral Models, and Robotics. This is a Summer 2026 paid 12-week internship opportunity. Please note that this internship will be a hybrid in-office role. The Team 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.
Requirements
- Currently enrolled in a Ph.D. program in Computer Science, Robotics, Machine Learning, or a related field.
- Strong background in machine learning, particularly in areas such as deep learning, generative models, reinforcement learning, or probabilistic modeling.
- Demonstrated experience with one or more of the following: World models (e.g., latent dynamics, diffusion-based models), Model-based RL or decision-making, 3D perception or sensor fusion, and Large-scale simulation for robotics or autonomous systems.
- Prior publication(s) in top-tier conferences (NeurIPS, ICLR, ICML, CVPR, ICRA, CoRL, etc.)
- Proficiency with Python and PyTorch.
Nice To Haves
- Familiarity with AWS services (S3, EC2, and SageMaker) and open-source driving datasets (nuScenes, Waymo, Argoverse, etc.) is a plus.
- Please include links to any relevant open-source contributions or technical project write-ups with your application.
Responsibilities
- Conduct original research in one or more areas: world modeling, multi-agent interaction, reinforcement learning, perception, or simulation-to-reality transfer.
- Collaborate closely with full-time researchers on the design, training, and evaluation of learning-based driving systems.
- Contribute to building and experimenting with task-aware, multi-modal, and uncertainty-aware models.
- Develop and evaluate prototypes in closed-loop simulation environments and, time permitting, on high-performance autonomous driving hardware.
- Present research findings through internal talks and work towards a top-tier academic publication.
- Integrate and work with large-scale datasets (open-source and internal).
Benefits
- TRI offers a generous benefits package including medical, dental, and vision insurance, and paid time off benefits (including holiday pay and sick time).
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What This Job Offers
Career Level
Intern
Education Level
Ph.D. or professional degree
Number of Employees
101-250 employees
