Senior Manager, Machine Assisted Cognition
Los Altos, CA /
Exploratory Research – Machine Assisted Cognition /
At Toyota Research Institute (TRI), we’re working to build a future where everyone has the freedom to move, engage, and explore with a focus on reducing vehicle collisions, injuries, and fatalities. Join us in our mission to improve the quality of human life through advances in artificial intelligence, automated driving, robotics, and materials science. We’re dedicated to building a world of “mobility for all” where everyone, regardless of age or ability, can live in harmony with technology to enjoy a better life. Through innovations in AI, we’ll help…
- Develop vehicles incapable of causing a crash, regardless of the actions of the driver.
- Develop technology for vehicles and robots to help people enjoy new levels of independence, access, and mobility.
- Bring advanced mobility technology to market faster.
- Discover new materials that will make batteries and hydrogen fuel cells smaller, lighter, less expensive and more powerful.
- Develop human-centered AI systems to augment (not replace) human decision making to increase the quality of decisions (e.g. mitigate cognitive biases) and/or to facilitate faster innovation cycles.
Our work is guided by a dedication to safety – in both what we research and how we perform our research our goal is 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 environment with forward-thinking people who enjoy solving tough problems and the financial backing to successfully achieve our goals. Come work with TRI if you’re interested in transforming mobility through designing technology for safer cars, enabling the elderly to age in place, or designing alternative fuel sources. Start your impossible with us.
TRI’s Machine Assisted Cognition (MAC) team is developing AI systems to augment (not replace) human decision making. In particular, MAC is advancing the intersection between behavioral science, machine learning, human-computer interaction, and causal inference to enhance human decision making. MAC will achieve this through simultaneously:
1) Conducting experiments on the mechanisms underlying decision making to build predictive models of human behavior, and
2) Conducting research on understanding those decisions, including new ways to engage and interact with those models, and investigating the nature of understanding information uncovered in our models.
- Manage research scientists conducting cutting-edge research at the intersection of behavioral science, AI, HCI as it relates to decision making resulting in peer-reviewed publications and/or patents
- Contribute to the recruitment, development, and retention of the overall team
- Guide research scientists to develop their long term careers by providing feedback and creating opportunities for professional growth and development
- Collaborate closely with MAC’s leadership to inform and execute the research strategy of the department
- Balance team management with a hands-on contribution to team projects
- Degree in Psychology, Behavioral Economics, Computer Science, Engineering, Information Sciences or equivalent. Ph.D. preferred.
- Experience in interdisciplinary research in these areas
- Strong research background, including top-tier peer-reviewed publications.
- 5+ years of people management experience in cross-functional settings
- Proven leadership track record, including influential communication skills that inspires teammates, enrolls cross-functional teams, engages senior leadership, and delivers results
Please add a link to Google Scholar and include a full list of publications when submitting your CV to this position.
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