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 Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavioral Models, and Robotics. This is a summer 2025 paid 12-week internship opportunity. Please note that this internship will be a hybrid in-office role. The Mission We are working to create general-purpose robots capable of accomplishing a wide variety of dexterous tasks. To do this, our team is building general-purpose machine learning foundation models for dexterous robot manipulation. These models, which we call Large Behavior Models (LBMs), use generative AI techniques to produce robot action from sensor data and human request. To accomplish this, we are creating a large curriculum of embodied robot demonstration data and combining that data with a rich corpus of internet-scale text, image, and video data. We are also using high-quality simulation to augment real world robot data with procedurally-generated synthetic demonstrations. The Team The Large Behavior Models Team's charter is to push the frontiers of research in robotics and machine learning to develop the future capabilities required for general-purpose robots able to operate in unstructured environments such as homes! Our Computer Vision team is looking for Research Interns with experience in areas such as Generalizable Representation Learning, Video Understanding, Spatio-Temporal World Models, Unsupervised Object Discovery, Differentiable Rendering, Neural Implicit Representations, Generative Models and Self-Supervised Learning. We are aiming to push the boundaries of scene reconstruction methods to enable the safe and effective usage of large robotic fleets, simulation, and prior knowledge (geometry, physics shown experience, behavioral science), not only for automation but also for human augmentation, working towards Principle-Centric Artificial Intelligence (AI) for Embodied Foundation Models, in the context of Large Behavior Models (LBMs).