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, Large Behavioral Models, and Robotics.

This is a summer 2025 paid 12-week internship opportunity with the HID team in the Platform Research department at TRI. Please note that this internship will be an in-office role based in Los Altos, CA.

The Team

The Human Interactive Driving Research group is focused on designing the future of advanced safety systems, pushing the envelope of safety, driver experience, and automation. Our team consists of cognitive scientists, computer scientists, software engineers, mechanical and electrical engineers, vehicle dynamics experts, designers, and more. We leverage multiple simulation and physical platforms to explore novel interfaces, algorithms, and safety technologies.

The Internship

The HID group is developing next-generation training and assessment tools for performance driving and beyond. We are looking into expanding our driving simulation technology by generating novel driving courses, including layout and other features, based on individual drivers’ skill levels, past performance, and long-horizon strategy development. These tracks may also be used to train autonomous and shared autonomy artificial agents. We are looking for a summer research intern in HQ to work on this effort, with the aim of approaching this as a research challenge for combining generative AI and human-factors research.

The individual will contribute to one or more high-level research focus areas:

- Procedural track generation using generative AI

- Dynamic content creation for CARLA-based driving simulator

- Driver skill assessment

The intern will be expected to work hands-on with a physical simulation system, create working code prototypes, interact frequently with team members, transfer code, design validation experiments, and participate in writing a paper describing the findings and publishing the work.

The ideal individual should be able to distill high-level project goals into an actionable work plan, possess strong skills in generative AI, and have good knowledge of ROS2 and the CARLA driving simulator.

Prior experience in cyber-physical systems, human-subjects research, and data analysis is a plus.

Qualifications

Currently pursuing a Ph.D. in Computer Science, Robotics, Human-Robot Interaction, or related fields
Experience in generative AI, whether LLMs with non-language tokens or diffusion models
Game development experience: Unreal, Unity, Godot, etc. and/or simulation development experience: CARLA, Sumo, Gazebo, AirSim, etc.
Strong software engineering skills (C++/Python preferred) and analysis/debugging robotic systems
Experience working in a shared codebase with multiple collaborators and reviewing others’ code
Strong written and oral communication skills
Experience in working in multi-disciplinary teams. You will be working cross-functionally with UX/UI designers, human-factors researchers, and cognitive scientists.
Must have a high level of self-initiative to prioritize and manage workload and meet project deadlines in a dynamic environment

Bonus Qualifications

Prior experience in ROS / ROS2
Previous experience with human subjects or human-centric research
Prior experience in scientific Python, R, or similar statistical analysis tools

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.

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Human Interactive Driving Research Intern

Platform Research

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