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 in Energy & Materials, Human-Centered AI, Human Interactive Driving, and Robotics. This is a summer 2025 paid 12-week internship opportunity with the HID team in the EPIC (Extreme Performance Intelligent Control ) department at TRI. Please note that this internship will be a hybrid in-office role based in Los Altos, CA. 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 are pursuing a cooperative approach to high-performance driving by developing predictive models and control frameworks for extreme vehicle maneuvering that match or exceed the skills of expert drivers. We envision a world where these tools allow each vehicle to support its driver, creating a safe and enjoyable experience for all. The Internship We are seeking a motivated intern to join our shared control driving team, focusing on cutting-edge research to ensure safe and effective human-AI collaboration for the next generation of advanced driver assistance systems. Potential research areas include developing novel planning and control algorithms to guarantee safety amid challenging driving scenarios, improving performance of existing shared control algorithms under uncertain conditions, and implementing data-driven/ML approaches to shared control with safety guarantees. This role provides an exciting opportunity to explore approaches to human-AI pairing that support safe, intuitive, and responsive shared 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 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.
\n ResponsibilitiesWork with researchers to develop and then undertake a well-scoped research project in a relevant areaExtend existing controls/AI/ML algorithms or design new algorithms for shared control with a human driver at a vehicle's performance limitsExplore approaches to formalize guarantees of safety for shared control algorithmsImplement algorithms on a full scale vehicle research platformPublish your original research at a high impact conference QualificationsPh.D. or M.S. student in relevant fields - ML/AI, robotics, computer science, mechanical engineering, aerospace engineering, or similarProficient in scientific Python, Unix, and robotic frameworks (e.g. ROS2.0).Knowledge of nonlinear system control, optimal control, statistical inference and estimation Vehicle dynamics knowledge is a plusExperience working on joint scientific and engineering projectsFamiliarity with or interest in racing or high-performance driving is a plus
\nPlease add a link to Google Scholar and include a full list of publications when submitting your CV to this position. The pay range for this position at commencement of employment is expected to be between $45 and $65/hour for California-based roles; however, base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. Note that TRI offers a generous benefits package including vacation and sick time. Details of participation in 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.
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