Human Interactive Driving Research Intern, Learning-Based Control for Safe Autonomous Driving

Toyota Research Institute • Los Altos, CA

5d • Hybrid

About The Position

Toyota Research Institute (TRI) is hiring a paid, 12-week intern for its Extreme Performance Intelligent Control team. The team develops vehicle safety and performance techniques using machine learning, optimization, and control theory, combining physics-based optimal control with data-driven learning. Its goal is to build interpretable controllers that adapt to uncertainty and match or exceed expert drivers.

The intern will conduct research combining machine learning, physical system knowledge, and control theory to develop reliable autonomous-vehicle controllers. Research may include learning-based control methods that enforce forward invariance, stability, and constraint satisfaction, as well as incorporating vehicle dynamics and other physical knowledge into learning and control for challenging driving scenarios. The intern will work with professional researchers on a scoped research project, implement algorithms on a full-scale vehicle research platform, and work toward publishing original research at a high-impact conference. The internship is hybrid and based at TRI headquarters in Los Altos, California.

Requirements

• Be an M.S. or Ph.D. student in a relevant field, such as machine learning, artificial intelligence, robotics, computer science, mechanical engineering, aerospace engineering, or a similar field.
• Be proficient in scientific Python, Unix, and robotic frameworks such as ROS2.0.
• Have knowledge of machine learning, nonlinear system control, and optimal control.
• Have experience working on joint scientific and engineering projects.
• Include links to relevant open-source contributions or technical project write-ups with the application.

Nice To Haves

• Vehicle dynamics knowledge.
• Familiarity with or interest in racing or high-performance driving.
• Relevant publications in the listed fields.
• Good collaboration skills.

Responsibilities

• Work with researchers to develop and undertake a well-scoped research project in a relevant area.
• Extend existing controls, AI, or machine-learning algorithms, or design new algorithms for control at a vehicle’s performance limit.
• Explore approaches to formalize safety guarantees for machine-learning algorithms.
• Implement algorithms on a full-scale vehicle research platform.
• Publish original research at a high-impact conference.

Benefits

• Medical, dental, and vision insurance.
• Paid time off, including holiday pay and sick time.
• Competitive compensation.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern