Research Intern: Robust Robotic Manipulation - Honda Research Institute USA

Research Intern: Robust Robotic Manipulation

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Research Intern: Robust Robotic Manipulation

Job Number: P26INT-26
Honda Research Institute USA (HRI-US) is seeking a self-motivated Ph.D. student to join the Intelligence Robotics Research Division as a summer intern. The intern will conduct research on robust, contact-rich dexterous manipulation, with a focus on methods that detect, prevent, and recover from failures of learned policies.
San Jose, CA

 

Key Responsibilities

 
  • Formulate and develop novel algorithms for robust manipulation, including but not limited to policy performance characterization, failure reasoning, post-training (e.g., RL fine-tuning), and recovery policy methods.
  • Develop methods that utilize multimodal sensing (vision, proprioception, tactile) to prevent and recover from policy failures.
  • Implement and validate methods in simulation and on real robot hardware.
  • Contribute to HRI's patent portfolio and publish research results when applicable at top-tier conferences and journals in robotics and machine learning. 
  • Communicate progress through presentations and written reports.

 

Minimum Qualifications

 
  • Currently enrolled in a Ph.D. program in Computer Science, Robotics, Electrical or Computer Engineering, Machine Learning, or a related field.
  • Strong background in robot learning and core robotics concepts (e.g., kinematics, dynamics, control).
  • Research experience in at least one relevant area, such as failure detection, recovery methods, or policy fine-tuning.
  • Proficiency in Python and experience with robotics physics simulators (e.g., MuJoCo, Isaac Sim).
  • Ability to independently formulate research questions, design experiments, and analyze results.
  • Strong written and verbal communication skills and the ability to work effectively in a collaborative research environment.

 

Bonus Qualifications​

  • Experience with reinforcement learning, imitation learning, multimodal learning, and/or state estimation.
  • Experience deploying learned policies on real robots, including sim-to-real transfer and real-world data collection.
  • Experience with dexterous multi-fingered hands, contact-rich manipulation, and/or tactile sensing.
  • Publications at relevant venues such as ICRA, IROS, CoRL, RSS, CVPR, NeurIPS, etc.

 

Years of Work Experience Required   0
Desired Start Date  May 2027
Internship Duration  3 Months
Position Keywords  Robotic Manipulation, Robot Learning, Failure Reasoning, Multi-modal Sensing 

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- Recent CV 
- A cover letter highlighting relevant background (Optional)

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