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 advancing the state of the art in AI, robotics, driving, and material sciences. This is a paid 12-week internship opportunity and is a hybrid, in-office role. Here’s a glimpse into the Internship experience from some of our TRI interns! 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 advancing the state of the art in AI, robotics, driving, and material sciences. This is a paid 12-week internship opportunity and is a hybrid, in-office role. Here’s a glimpse into the Internship experience from some of our TRI interns! The Team Within the Extreme Performance Intelligent Control team, we are developing techniques to advance vehicle safety and performance capabilities using tools from machine learning, optimization, and control theory. We pursue a hybrid approach to high-performance driving that unites physics-based optimal control with data-driven learning. By embedding vehicle dynamics and optimization structure into learned controllers, we aim to build systems that adapt to uncertainty and match or exceed expert drivers while retaining the interpretability and guarantees of classical methods. The Internship We are seeking a motivated intern to join our team, focusing on cutting-edge research combining machine learning with physical system knowledge and control theory to develop reliable controllers for autonomous vehicles. Potential research areas include designing learning-based control methods that enforce forward invariance, stability, and constraint satisfaction; and incorporating vehicle dynamics and other physical knowledge into learning and control amid challenging driving scenarios. This role provides an exciting opportunity to explore approaches to machine learning for control that support safe, intuitive, and responsive driving systems. Along the way you will apply your knowledge to tackle novel research questions and work towards a publication with professional researchers. The internship will be in our headquarters in Los Altos, CA and includes competitive compensation befitting the challenging, but fun, nature of the research work at TRI. Applicants with relevant publications in the fields above and good collaboration skills are highly encouraged to apply. The Team Within the Extreme Performance Intelligent Control team, we are developing techniques to advance vehicle safety and performance capabilities using tools from machine learning, optimization, and control theory. We pursue a hybrid approach to high-performance driving that unites physics-based optimal control with data-driven learning. By embedding vehicle dynamics and optimization structure into learned controllers, we aim to build systems that adapt to uncertainty and match or exceed expert drivers while retaining the interpretability and guarantees of classical methods. The Internship We are seeking a motivated intern to join our team, focusing on cutting-edge research combining machine learning with physical system knowledge and control theory to develop reliable controllers for autonomous vehicles. Potential research areas include designing learning-based control methods that enforce forward invariance, stability, and constraint satisfaction; and incorporating vehicle dynamics and other physical knowledge into learning and control amid challenging driving scenarios. This role provides an exciting opportunity to explore approaches to machine learning for control that support safe, intuitive, and responsive driving systems. Along the way you will apply your knowledge to tackle novel research questions and work towards a publication with professional researchers. The internship will be in our headquarters in Los Altos, CA and includes competitive compensation befitting the challenging, but fun, nature of the research work at TRI. Applicants with relevant publications in the fields above and good collaboration skills are highly encouraged to apply. 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. 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. Please include links to any relevant open-source contributions or technical project write-ups with your application. The pay range for this position at commencement of employment is expected to be between $45 and $65/hour for California-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, a candidate's experience, skills, job-related knowledge, and market location. TRI offers a generous benefits package including medical, dental, and vision insurance, and paid time off benefits (including holiday pay and sick time). Additional details regarding these benefit plans will be provided if an employee receives an offer of employment. Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information. TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant’s race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.

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

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