Postdoctoral Researcher, Large Behavior Models

Los Altos , United States
full-time

AI overview

Collaborate with the Learning From Videos team to develop advanced algorithms for multi-modal and 4D reasoning, focusing on real-world applications in robotics.
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 Automated Driving, Energy & Materials, Human-Centered AI, Human Interactive Driving, Large Behavior Models, and Robotics. 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. Base pay offered will depend on multiple individualized factors, including, but not limited to, business or organizational needs, market location, job-related knowledge, skills, and experience. TRI offers a generous benefits package including medical, dental, and vision insurance, and paid time off benefits (including holiday pay and sick time). Additional details regarding these benefit plans will be provided if an employee receives an offer of employment.

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    The Toyota Research Institute (TRI) is building a new approach to mobility and pioneering the technologies that will drive its future. TRI is applying artificial intelligence to help Toyota produce cars in the future that are safer, more accessible and...

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    Salary
    $176,000 – $264,000 per year
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