Toyota Research Institute
Postdoctoral Researcher, Large Behavior Models
Toyota Research Institute, Los Altos, California, United States, 94024
The Team
The Learning From Videos (LFV) team in the Robotics division focuses on the development of foundation models capable of leveraging large-scale multi-modal (RGB, depth, flow, semantics, bounding boxes, tactile, audio, etc) data from multiple domains (driving, robotics, indoors, outdoors, etc) to improve the performance of downstream tasks. This paradigm targets training scalability, since data from multiple modalities can be equally leveraged to learn useful data-driven priors (3D geometry, physics, dynamics, etc) for world understanding. Our topics of interest include, but are not limited to, Video Generation, World Models, 4D Reconstruction, Multi-Modal Models, Multi-View Geometry, Data Augmentation, and Video-Language-Action models, with a primary focus on embodied applications. We are aiming to make progress on some of the hardest scientific challenges around spatio-temporal reasoning, and how it can lead to the deployment of autonomous agents in real-world unstructured environments. The Postdoc This year-long postdoctoral research position will be highly integrated into our team, with hands in both ongoing and new research and development threads in the areas of: 4D World Models Physical and Embodied Intelligence Multi-Modal Learning This researcher will have the opportunity to work collaboratively with our team at TRI on high-risk, high-reward projects, pushing forward our understanding of spatio-temporal reasoning and zero-shot generalization. This is a research-focused position, targeting the development of methods and techniques that can solve real-world problems. We welcome you to join a positive, friendly, and enthusiastic team of researchers, where you will contribute to helping people gain and maintain independence, access, and mobility. We work closely with other Toyota affiliates and actively collaborate towards research publications and the productization of our developed technologies. Responsibilities Develop, integrate, and deploy algorithms for Multi-Modal and 4D reasoning targeting physical applications. Handle the ingestion of large-scale datasets for training, including streaming, online, and continual learning. Invent and deploy innovative solutions at the intersection of machine learning, computer vision, and robotics that improve the real-world performance of useful tasks. Work closely with robotics and machine learning researchers and engineers to understand theoretical and practical needs. Follow best practices producing maintainable code, both for internal use as well as for open-sourcing to the scientific community. Qualifications Ph.D. in a relevant technical field. A strong background in computer vision and its applications to robotics and embodied systems. A standout colleague with strong communication skills, and an ability to learn from others and contribute back to the scientific community with publications or open source code. Passionate about assisting and amplifying older adults and those in need through dexterous manipulation, human-robot collaboration, and physical assistance innovation. Bonus Qualifications Spatio-temporal (4D) computer vision, including multi-view geometry, 3D/4D reconstruction, video generation, self-supervised learning, occlusion reasoning, etc. Large-scale training of multi-modal deep learning methods, both in terms of dataset sizes and model complexity, context length extension, and efficient attention, distributed computing, etc. Application of machine learning and computer vision to embodied applications. The pay range for this position at commencement of employment is expected to be between $176,000 and $264,000/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. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.
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The Learning From Videos (LFV) team in the Robotics division focuses on the development of foundation models capable of leveraging large-scale multi-modal (RGB, depth, flow, semantics, bounding boxes, tactile, audio, etc) data from multiple domains (driving, robotics, indoors, outdoors, etc) to improve the performance of downstream tasks. This paradigm targets training scalability, since data from multiple modalities can be equally leveraged to learn useful data-driven priors (3D geometry, physics, dynamics, etc) for world understanding. Our topics of interest include, but are not limited to, Video Generation, World Models, 4D Reconstruction, Multi-Modal Models, Multi-View Geometry, Data Augmentation, and Video-Language-Action models, with a primary focus on embodied applications. We are aiming to make progress on some of the hardest scientific challenges around spatio-temporal reasoning, and how it can lead to the deployment of autonomous agents in real-world unstructured environments. The Postdoc This year-long postdoctoral research position will be highly integrated into our team, with hands in both ongoing and new research and development threads in the areas of: 4D World Models Physical and Embodied Intelligence Multi-Modal Learning This researcher will have the opportunity to work collaboratively with our team at TRI on high-risk, high-reward projects, pushing forward our understanding of spatio-temporal reasoning and zero-shot generalization. This is a research-focused position, targeting the development of methods and techniques that can solve real-world problems. We welcome you to join a positive, friendly, and enthusiastic team of researchers, where you will contribute to helping people gain and maintain independence, access, and mobility. We work closely with other Toyota affiliates and actively collaborate towards research publications and the productization of our developed technologies. Responsibilities Develop, integrate, and deploy algorithms for Multi-Modal and 4D reasoning targeting physical applications. Handle the ingestion of large-scale datasets for training, including streaming, online, and continual learning. Invent and deploy innovative solutions at the intersection of machine learning, computer vision, and robotics that improve the real-world performance of useful tasks. Work closely with robotics and machine learning researchers and engineers to understand theoretical and practical needs. Follow best practices producing maintainable code, both for internal use as well as for open-sourcing to the scientific community. Qualifications Ph.D. in a relevant technical field. A strong background in computer vision and its applications to robotics and embodied systems. A standout colleague with strong communication skills, and an ability to learn from others and contribute back to the scientific community with publications or open source code. Passionate about assisting and amplifying older adults and those in need through dexterous manipulation, human-robot collaboration, and physical assistance innovation. Bonus Qualifications Spatio-temporal (4D) computer vision, including multi-view geometry, 3D/4D reconstruction, video generation, self-supervised learning, occlusion reasoning, etc. Large-scale training of multi-modal deep learning methods, both in terms of dataset sizes and model complexity, context length extension, and efficient attention, distributed computing, etc. Application of machine learning and computer vision to embodied applications. The pay range for this position at commencement of employment is expected to be between $176,000 and $264,000/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. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records for employment.
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