Research Scientist - Shared Control

Key Skills

AWS, Computer Vision (CV), Framework, NeurIPS, Python Programming, PyTorch, Reinforcement Learning

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

Our Extreme Performance Intelligent Control team is looking for a Research Scientist with experience in Shared Control and at least one of the following areas; Reinforcement Learning/Data Driven Control, or Human Behavioral Modeling. We are aiming to make progress on a key challenge to unlock the full potential of artificial intelligence in a human world: how do we design vehicles that best amplify drivers of all skill levels.

As a Research Scientist, you will work with a multidisciplinary team proposing, conducting, and transferring innovative research. You will use real-world and simulated sensory data to solve open problems, publish at top academic venues, and test your ideas in the real world (possibilities include our innovative motion simulators and test vehicles of course!). You will help to transfer and ship our most successful algorithms and models towards real-world advanced assistance systems, touching millions of lives.

Responsibilities

• Conduct ambitious research that solves open problems of high practical value and validate it in real-world systems.
• Push the boundaries of knowledge and the state of the art in Shared Control for driving.
• Implement code and test in simulation and on vehicles.
• Partner with a multidisciplinary team including other research scientists and engineers across the Human Interactive Driving team, TRI, Toyota, and our university partners.
• Present results in verbal and written communications, internally, at top international venues, and via open source contributions to the community.

Qualifications

• Bachelor’s or Master’s degree in a quantitative field (e.g. Computer Science, Mathematics, Physics, Engineering, Chemistry). Ph.D. or deep expertise in one key area (Reinforcement Learning/Data Driven Control, Human Behavioral Modeling, or Shared Control) or related field.
• Consistent track record of publishing at high-impact conferences/journals (ICLR, NeurIPS, ICML, CoRL, RSS, ICRA, IROS, CDC, ACC, IFAC, AVEC etc.).
• Proficient at scientific Python, Unix, and a common DL framework (preferably PyTorch). Experience with distributed learning (especially on AWS) is a plus.
• Experience with vehicle dynamics / autonomous vehicle control / driver modeling/ testing on real hardware is a major plus.
• You are a reliable team-player. You care about openness and delivering with integrity.

Please 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 $151,800 and $210,000/year 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 401(k) eligibility and various paid time off benefits, such as vacation, sick time, and parental leave) and an annual cash bonus structure. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.

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