Autonomous Driving Research Intern: Learning-Based Control

Toyota Research Institute Inc.; Los Altos (CA); Hybrid; USD 62,000 - 90,000; Part time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

Paid Time Off

Job summary

Toyota Research Institute, Inc. seeks a motivated intern to join the Extreme Performance Intelligent Control team, blending machine learning with control theory to develop reliable controllers for autonomous vehicles.

You will work on forward invariance, stability, and safety guarantees, applying vehicle dynamics in challenging driving scenarios. This 12-week paid internship is hybrid and based at TRI headquarters in Los Altos, CA, with opportunities to publish and collaborate with researchers.

Qualifications

• Ph.D. or M.S. student in relevant fields—ML/AI, robotics, computer science, mechanical engineering, aerospace engineering, or similar.
• Proficient in scientific Python, Unix, and robotic frameworks (e.g. ROS2.0).
• Knowledge of machine learning, nonlinear system control, and optimal control; vehicle dynamics knowledge is a plus.
• Experience working on joint scientific and engineering projects.
• Familiarity with or interest in racing or high-performance driving is a plus.

Responsibilities

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

Skills

Scientific Python

Unix

ROS 2.0

ML knowledge

Nonlinear control

Optimal control

Joint projects

High-performance driving interest

Education

Ph.D./M.S. student in ML/AI, robotics, CS, ME, AE

Job description

Toyota Research Institute, Inc. seeks a motivated intern to join the Extreme Performance Intelligent Control team, blending machine learning with control theory to develop reliable controllers for autonomous vehicles.

You will work on forward invariance, stability, and safety guarantees, applying vehicle dynamics in challenging driving scenarios. This 12-week paid internship is hybrid and based at TRI headquarters in Los Altos, CA, with opportunities to publish and collaborate with researchers.