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Research Scientist - Shared Control

Company

Toyota Research Institute

Address Los Altos, CA, United States
Employment type FULL_TIME
Salary
Category Research Services
Expires 2023-09-04
Posted at 9 months ago
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.


Through innovations in AI, we:


  • Bring advanced mobility technology to market faster.
  • Discover new materials that will make drive batteries and hydrogen fuel cells smaller, lighter, less expensive, and more powerful.
  • Develop technology for vehicles and robots to help people enjoy new levels of independence, access, and mobility.
  • Develop vehicles incapable of causing a crash, regardless of the actions of the driver.


Our work is guided by a dedication to safety – in how we research, develop, and validate the performance of technology to benefit society. As a subsidiary of Toyota, TRI is fueled by a diverse and inclusive community of people who carry invaluable leadership, experience, and ideas from industry-leading companies.


Over half of our technical team carries PhD degrees. We’re continually searching for the world’s best talent ‒ people who are ready to define the new world of mobility with us! We strive to build a company that helps our people thrive, achieve work-life balance, and bring their best selves to work. At TRI, you will have the opportunity to enjoy the best of both worlds ‒ a fun start up environment with resourceful people who enjoy solving global problems and the financial backing to successfully achieve our goals. If you’re passionate about working with inquisitive people to make cars safer, enable the older population to age in place, or design alternative fuel sources, TRI is the place for you. ‒ Start your impossible with us.


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


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


  • You are a reliable team-player. You care about openness and delivering with integrity.
  • 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.
  • 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.).


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.


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.