Research Intern: Online Learning for Dexterous Manipulation - Honda Research Institute USA

Research Intern: Online Learning for Dexterous Manipulation

Your application is being processed

Research Intern: Online Learning for Dexterous Manipulation

Job Number: P25INT-17
​Honda Research Institute USA (HRI-US) is seeking a self-motivated PhD student to join our Intelligence Robotics Research Division as a summer intern. Our research focuses on online learning for dexterous manipulation in real-world environments, aiming to advance adaptive and data-efficient robotic learning. The successful candidate will work on topics such as online model improvement to reduce the sim-to-real gap or increasing efficiency in real-world reinforcement learning frameworks.
San Jose, CA

 

Key Responsibilities

 
  • Develop novel algorithms for online learning of dexterous manipulation skills in the real-world focusing on aspects such as learning efficiency, model adaptation, and robustness.
  • Design and perform systematic experiments on real robotic hardware to validate and compare developed methods.
  • Contribute to the software stack by developing efficient and reliable components.
  • Document findings and contribute to internal research reports
  • Contribute to the portfolio of patents, and publish research results when applicable at top-tier conferences and journals in robotics and machine learning.

 

Minimum Qualifications

 
  • Currently enrolled in a Ph.D. program with significant experience in Robotics, Computer Science, Mechanical Engineering, or a related field.
  • Experience with physics simulators (MuJoCo preferred).
  • Experience in Reinforcement Learning (RL) and/or Model Predictive Control (MPC).
  • Hands-on experience in implementation and experimentation with real robotic hardware.
  • Proficiency in Python and C++.

 

Bonus Qualifications​

  • Hands-on experience with multi-fingered robotic hands.
  • Experience in sample efficient, online learning.
  • Experience with differentiable physics simulators.
  • Experience with GPU-accelerated simulation and domain randomization.

 

Years of Work Experience Required  0
Desired Start Date 5/11/2026
Internship Duration 3 Months
Position Keywords ​Dexterous manipulation, Online Learning, Reinforcement Learning, Model Predictive Control

Alternate Way to Apply

Send an e-mail to careers@honda-ri.com with the following:
- Subject line including the job number(s) you are applying for 
- Recent CV 
- A cover letter highlighting relevant background (Optional)

Please, do not contact our office to inquiry about your application status.