Verified current Internship

Robotics Research Intern - Post-Training

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 th

Internship Full source details
Tri Source published Sep 20, 2026 Verified 10 hours ago
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Overview

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 th

Complete internship details

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. This is a paid 12-week internship opportunity and is a hybrid, in-office role. Here’s a glimpse into the Internship experience from some of our TRI interns!

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.

Interest in open research problems involving large-scale machine learning grounded in physical systems.

Proficiency in Python and a deep-learning framework such as PyTorch.

Ability to collaborate effectively with researchers and engineers and communicate research findings clearly.

Experience with pretrained generalist policies, foundation models, or large-scale robot-learning systems.

Familiarity with offline or online reinforcement learning, DAgger, interactive learning, or human-in-the-loop methods.

Experience with simulation, sim-to-real transfer, policy distillation, or robotic manipulation.

Experience with learned world models, model-based reinforcement learning, or planning.

Publication record or interest in publishing at leading venues such as CoRL, NeurIPS, ICLR, ICML, RSS, ICRA, IROS, or related conferences and journals.

Interest in translating fundamental research into reliable methods that can be evaluated on real robotic systems and practical downstream tasks.

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