Robotics Intern, Post-Training and Continual Learning

Toyota Research Institute, Los Altos, CA

The role

Our research interests include reinforcement learning, imitation learning, human-in-the-loop learning, simulation, world models, policy distillation, and large-scale robot learning. We aim to advance the scientific foundations of policy adaptation while developing methods that may ultimately be evaluated or deployed within internal research projects involving real-world industrial tasks.

Potential research directions include, but are not limited to:

Offline-to-online reinforcement learning

DAgger, imitation learning, and human-in-the-loop policy improvement

Sim-to-real policy distillation and adaptation

Policy improvement, planning, or data generation using world models

Data-efficient adaptation to new tasks and environments

What you 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.

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.

Bonus Qualifications -

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.

Please include a link to your Google Scholar profile and a complete publication list when submitting your CV for this position.

The pay range for this position at commencement of employment is expected to be between $45 and $65/hour for California-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, 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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Robotics Intern, Post-Training and Continual Learning

The role

Robotics Intern, Post-Training and Continual Learning

The role

What you need

The Team

About Toyota Research Institute

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