Research Intern: Memory for Dexterous Robotic Manipulation

Honda Research Institute USA; San Jose (CA); On-site; USD 20,000 - 27,000; Full time

Job summary

Honda Research Institute USA in San Jose, CA seeks a Research Intern to advance memory representations for dexterous manipulation using multi-modal sensory data. The role focuses on long-horizon, contact-rich tasks and developing latent memories to inform robot policies.

Strong background in representation learning and sequence modeling is required, with experiments in both simulation and real hardware. The position emphasizes publication and patent contribution, with opportunities to publish at

Qualifications

• Ph.D. or MS in robotics, computer science, or a related field.
• Experience with representation learning using multi-modal robot data (e.g., RGB, RGB-D, and tactile).
• Experience with learned state-space models.
• Experience with policy deployment on real-world robots.
• Experience with robotic simulators (e.g., Isaac Gym or MuJoCo).
• Proficient with Python and C++.
• Proficient with PyTorch.
• Experience with Robot Operating System (ROS2).

Responsibilities

• Develop memory representation for long-horizon, contact-rich manipulation for multi-fingered robot hand.
• Design training objectives that enforce information retention over a long-horizon.
• Collect and process data to conduct representation training, and evaluate them on downstream robot policies.
• Implement baselines and perform benchmark evaluations (hardware and simulation).
• 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.

Skills

Representation learning

Multi-modal data

Sequence modeling

Policy deployment on real robots

Python

C++

PyTorch

ROS2

Education

Ph.D. or MS in robotics, CS, or related field

Tools

Python

C++

PyTorch

ROS2

MuJoCo

Isaac Gym

Job description

Honda Research Institute USA in San Jose, CA seeks a Research Intern to advance memory representations for dexterous manipulation using multi-modal sensory data. The role focuses on long-horizon, contact-rich tasks and developing latent memories to inform robot policies.

Strong background in representation learning and sequence modeling is required, with experiments in both simulation and real hardware. The position emphasizes publication and patent contribution, with opportunities to publish at