📅 Sep 17
Conduct computational and machine learning research on human-robot interaction, developing and validating data-efficient, robust approaches for collaboration, shared autonomy, and embodied interaction.
Postdoctoral Researcher, Post-Training and Continual Adaptation for Robotics
🕒 4 days ago
Reinforcement LearningImitation LearningRobot LearningPost-training
📜 Description
- Develop methods for post-training and adapting pretrained robot policies.
- Take a focused research question from initial formulation through experimental validation.
- Design experiments to evaluate policy improvement, adaptation, robustness, and retention of existing capabilities.
- Study how outcomes relate to robot experience and human effort.
- Collaborate with researchers and communicate findings through publications in leading robotics and machine learning venues.
🛠️ Requirements
- Ph.D. in robotics, machine learning, computer science, or a related field, completed by the start of the appointment.
- Strong research background in reinforcement learning, imitation learning, or related robot-learning methods, demonstrated through relevant publications.
- Strong programming and experimental skills, including experience with PyTorch or JAX and robotic systems.
- Ability to develop and carry out a scientific research plan collaboratively.
- Experience with robot foundation models, online adaptation, human feedback, or continual learning is especially relevant.
✨ Benefits
- Medical insurance
- Dental insurance
- Vision insurance
- 401(k) eligibility
- Paid vacation
- Paid sick time
- Paid parental leave
- Annual cash bonus structure
Full 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 advancing the state of the art in AI, robotics, driving, and material sciences.
The Opportunity
We are seeking a postdoctoral researcher to advance post-training and adaptation for generative robot policies. Our goal is to enable pretrained policies to improve task performance, adapt to human preferences, and acquire new behaviors from limited experience while preserving existing capabilities.
You will work closely with our robotics and machine learning researchers on a focused project, developing new methods and validating them through experiments in simulation and on real robots.
The Challenge
Pretrained robot policies can perform increasingly broad behaviors, yet improving them for new tasks, environments, and user needs remains difficult. Robot experience is limited, feedback can be imperfect, and adapting a policy can undermine capabilities it already has.
Research directions include learning efficiently from demonstrations, online interaction, and human feedback; using reinforcement learning and related methods to improve and customize pretrained policies; and retaining useful improvements across tasks and over time. The project will pursue a specific question within this agenda, shaped jointly around the researcher’s expertise and the team’s research priorities.
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 advancing the state of the art in AI, robotics, driving, and material sciences. The pay range for this position at commencement of employment is expected to be between $136,800and $196,650/year for Massachusetts-based roles. Base pay offered will depend on multiple individualized factors, including, but not limited to, a candidate's experience, skills, job-related knowledge, and market location. TRI offers a generous benefits package including medical, dental, and vision insurance, 401(k) eligibility, paid time off benefits (including vacation, sick time, and parental leave), and an annual cash bonus structure. Additional details regarding 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 or continued 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.Responsibilities
Design rigorous experiments to evaluate policy improvement, behavioral adaptation, robustness, and retention of existing capabilities relative to robot experience and human effort.
Collaborate with the research team and communicate findings through publications in leading robotics and machine learning venues.
Qualifications
Ph.D. in robotics, machine learning, computer science, or a related field, completed by the start of the appointment.
Strong research background in reinforcement learning, imitation learning, or related robot-learning methods, demonstrated through relevant publications.
Strong programming and experimental skills, including experience with deep learning frameworks such as PyTorch or JAX and with robotic systems.
Ability to develop and carry out a scientific research plan in collaboration with other researchers.
Experience with robot foundation models, online adaptation, human feedback, or continual learning is especially relevant.
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