About the role#
We are looking for two Research Interns to join our Robotics division for the Fall 2026 term. You will investigate open research questions regarding the post-training and adaptation of pretrained generalist robot policies. Our goal is to convert broad behavioral capabilities into policies that adapt quickly, learn from limited data, and perform consistently on demanding tasks. You will work closely with our researchers and engineers to produce meaningful scientific results, with the potential to publish at leading robotics or machine-learning venues.
What you'll do#
- Investigate open research questions in post-training and adaptation of pretrained generalist robot policies.
- Explore offline-to-online reinforcement learning and imitation learning methods.
- Work on sim-to-real policy distillation and adaptation methods.
- Engage in data-efficient adaptation to new tasks and environments.
- Collaborate with researchers and engineers to produce meaningful scientific results.
What you'll need#
- Currently pursuing a Ph.D. in Computer Science, Machine Learning, Robotics, or a related field.
- Research experience in robot learning, reinforcement learning, imitation learning, generative modeling, world models, or a related area.
- Proficiency in Python and a deep-learning framework such as PyTorch.
- Interest in open research problems involving large-scale machine learning grounded in physical systems.
- Ability to collaborate effectively with researchers and engineers.
Location & details#
- This is a full-time, paid internship based in Los Altos, California.
- The role is hybrid and requires in-office attendance.
- The term for this position is Fall 2026.
About Toyota Research Institute
Toyota Research Institute is a research organization founded in 2016. Based in Los Altos, California, it operates as a subsidiary of Toyota. The company focuses on artificial intelligence, robotics, automated driving, and material sciences. Its staff of approximately 485 employees works to develop technology for vehicles and robots while researching new materials for batteries and fuel cells.
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