Human Interactive Driving Intern – Uncertainty-Aware Control

Toyota Research Institute (TRI) is seeking a Research Intern to develop control, modeling, and/or perception methodologies for high-performance driving, leveraging machine learning, optimization, and control theory. The internship will involve experiments with high-performance vehicles on a closed racetrack and a hybrid in-office role in the Extreme Performance Intelligent Control team.

Requirements

• Develop novel uncertainty-aware control, modeling, or/and perception algorithms.
• Implement, deploy, and evaluate models and algorithms on high-performance cars.
• Present results in verbal and written communications at international conferences and internally.
• Ph.D. candidate working on related fields: optimization, machine learning, control, Bayesian modeling, computer vision, or related fields.
• Proficiency in at least one of the following: Python, C++, ROS(2), Pytorch, JAX.

Benefits

• Vacation and sick time