High-Performance Driving - ML & Control Research Intern

Key Skills

Aartificial intelligence, Design, Machine learning techniques, Optimization, Python Programming

Job Description

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 Robotics, Human-Centered AI, Human Interactive Driving, and Energy & Materials.

This is a Summer 2024 paid 12-week internship opportunity. Please note that this internship will be a hybrid in-office role.

The Team

Within the Extreme Performance Intelligent Control team, we are developing techniques to advance vehicle safety and performance capabilities using tools drawn from machine learning and optimal control. We are pursuing a cooperative approach to performance driving by developing both predictive models of driver behavior in demanding situations as well as control frameworks that can meet 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 fun-to-drive experience for all.

The Internship

In this project, we are broadly interested in developing new intelligent control methodologies for high-performance driving that account for uncertainty, e.g., stemming from uncertain friction properties, and that can learn from experience to improve performance and safety.

Responsibilities

• Design models with uncertainty quantification
• Design control techniques to efficiently gather data online and refine models
• Implement, deploy, and test models and algorithms on high-performance cars
• Publish original research

Qualifications

• Ph.D. candidate working on related fields - machine learning, robotics, control, optimization
• Research experience in at least one of the following: Bayesian learning, online learning, optimization, optimal control
• Strong programming skills
• Experience with Python and machine learning frameworks
• Experience in deploying algorithms on real-world platforms
• Excellent collaboration skills

Please include a link to Google Scholar and to a relevant publication or project when submitting your CV to this position. You can use the Portfolio URL section for these purposes.

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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