Human Interactive Driving Intern – World Models
Toyota Research Institute (TRI) is focused on improving the quality of human life through innovative research in automated driving and human-centered AI. The Human Interactive Driving Intern will conduct original research in machine learning and autonomous driving, collaborating with researchers to develop and evaluate models for driving systems.
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)
Skills
- 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
- Familiarity with AWS services (S3, EC2, and SageMaker) and open-source driving datasets (nuScenes, Waymo, Argoverse, etc.) is a plus
Benefits
- Medical, dental, and vision insurance
- Paid time off benefits (including holiday pay and sick time)
Company Overview
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