Toyota Research Institute (TRI) is developing new tools and capabilities to amplify the human experience and improve the quality of human life, specifically in the domain of automated and semi-autonomous driving systems, by creating AI approaches that challenge traditional methods for prediction, planning, and interaction with the driver, approaching the interaction as longer-term human-AI teaming.
Requirements
- Publication background in relevant venues in the field.
- Specific areas: Imitation/reinforcement learning (RL), control and decision theory, human behavior modeling and understanding, shared control, and computational tutoring.
- Frameworks: Pytorch/TensorFlow, and similar DL frameworks and tools.
- Coding: Python, experience working in a team on joint scientific projects.
- An ideal candidate can refine a topic and complete a scientific research plan in collaboration with the mentor and other researchers.
Responsibilities
- Perform research and publish in a relevant venue on relevant topics.
- Exploration of both computational and cognitive phenomena, working with a team of researchers to create new approaches for understanding, predicting, and interacting with humans.
- Work from approach inception and ideation to validation of the developed approaches.
Other
- Summer 2026 paid 12-week internship opportunity.
- hybrid in-office role.
- Ph.D. Student in related fields - ML/AI, robotics, human-centric AI, or computer vision.
- Applicants with relevant publications in these fields and good collaboration skills are highly encouraged to apply.
- Please add a link to Google Scholar to include a full list of publications when submitting your CV for this position.
