Toyota Research Institute
At Toyota Research Institute (TRI), we’re building a future where everyone has the freedom to move, engage, and explore with a focus on reducing vehicle collisions, injuries, and fatalities. Join us to improve the quality of human life through advances in artificial intelligence, automated driving, robotics, and materials science. We’re building a world of “mobility for all” where everyone, regardless of age or ability, can live in harmony with technology to enjoy better life through innovations in AI.
Our work is guided by a dedication to safety – in both what we research and how we perform our research 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 teams carry 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!
Our company strives to help our people thrive, achieve work-life balance, and bring their best selves to work. At TRI, you’ll have opportunity to enjoy the best of both worlds ‒ a fun environment with forward-thinking people solving tough problems and the financial backing to optimally achieve our goals. Come work with TRI and redefine mobility through crafting technology for safer cars, enabling the elderly to age in place, or designing alternative fuel sources. Start your impossible with us.
Our HASTEN (Helping Aging Society: Tactile Embodied Nudging) team bridges complementary research and engineering expertise in physical human-robot interaction, soft robotics, humanoid systems, software development, educational & entertainment electronics, and user-centered design. We’re working on highly compliant tactile “bubble” sensors and algorithms to put them to human-centered use, and innovating ways to physically support and amplify older adults with domestic manipulation skills, ensuring safe independent living respective to fall prevention. We envision development of contact-based guarding interaction algorithms that enable our bubblized soft robot to physically support an individual person and maintain their desired level of support by continuing to learn over time, using large amounts of data from contact-rich, critical interactions between our robot’s body, people, and the world.
Find opportunities for novel contact guard-based human-robot interactions derived from user needs of aging society
Collaborate cross functionally with roboticists, software engineers, and user experience researchers
Invent /Deploy innovative solutions at the intersection of hands-on, physical contact-based human-robot interaction, soft-robotics, tactile sensing, machine learning, and simulation for physically assisting humans in homes
Follow software practices producing maintainable code, including automated testing, CI, code style conformity, review
Develop and run experiments on real hardware
M.S. or Ph.D. (Robotics, Computer Science, HCI, Biomedical/Biomechanical Engineering, Human Factors, or related) OR equivalent practical experience
Expertise in physical contact guard assistance and interaction with humans and technical knowledge of human neuromechanical modeling and human body movement modeling
Experience with motion capture recording/motion analysis; familiarity with human biomechanics modeling software (OpenSim, AnyBody, etc.)
Expertise/Experience in machine learning around user behavioral modeling, adapting to individual user’s preference and preference changes over time
System integration experience around complex, open-ended, multi-functional projects
Strong software engineering skills (C++ /Python preferred) and analysis/debugging autonomous robotic systems
Prior work emphasizing user needs finding and User-centered Design process, including formative and summative user studies with end-users
Experience with qualitative and quantitative user research, including developing user study materials, IRB application, facilitation and interviewing, management of Personally Identifiable Information (PII), and statistical analysis
Strong communicator and ability to learn from others and contribute back to robotics community with publications and open source code
Passion for seeing robotics help humans and have a real-world, large-scale impact
Additional experience/knowledge in some or all of the following areas:
Experience working with older adults, specifically recording/analyzing gait
Experience in tactile sensing, modelling soft-contact, soft robotics
Experience applying machine learning to robotics, including around reinforcement, imitation, transfer learning
Experience integrating multimodal sensing into planning and control and development of sensor fusion methods.
Knowledge of optimization and sampling based planners for physical, reactive planning and control, trajectory optimization, coordinated whole-body control
Comfortable using Adobe Illustrator, Adobe Xd, Sketch, or a similar for task flows, wireframes, mockups
Comfortable using Adobe Premiere or similar software to produce stimuli or concept videos
Appetite to learn across functions
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