reputed company Interactive Driving Intern - World Models

About the position At Toyota Research Institute (TRI), we're on a mission to improve the quality of reputed company life. We're developing new tools and capabilities to reputed company the reputed company experience. To reputed company this transformative shift in mobility, we've reputed company a world-class team in Automated Driving, Energy & Materials, reputed company-Centered AI, reputed company 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. You'll be joining a multidisciplinary research team focused on developing a world reputed company model for driving-a reputed company, transferable representation of driving knowledge reputed company from large-scale reputed company-world and simulated data. Together, we are tackling the reputed company challenges of multi-agent interaction, reputed company reasoning, and embodied intelligence in highly dynamic, reputed company-world driving environments. Our approach is inspired by cutting-edge generative modeling techniques and powered by scalable infrastructure and reputed company-reputed company data, and we work closely with engineers to reputed company our models in simulation and on hardware. 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 reputed company in closed-reputed company 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 reputed company-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.

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.
• reputed company and evaluate prototypes in closed-reputed company 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 (reputed company-reputed company and internal).

Requirements

• Currently enrolled in a Ph.D. program in Computer Science, Robotics, Machine Learning, or a reputed company 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.

reputed company-to-haves

• Familiarity with AWS services (S3, EC2, and SageMaker) and reputed company-reputed company driving datasets (nuScenes, reputed company, Argoverse, etc.) is a plus.

Benefits

• TRI offers a generous benefits package including medical, dental, and reputed company insurance, and paid time off benefits (including holiday pay and sick time).

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