Key Responsibilities

• Research, ideate, and develop robotics systems that incorporate large language and vision-language models (LLMs/VLMs) to enable intelligent, human-interpretable planning and execution for real-world tasks.
• Conduct applied research in machine learning, including reinforcement learning and imitation learning, with a focus on contact-rich, dexterous manipulation and human-in-the-loop interaction.
• Implement and test algorithms in simulation environments (e.g., Isaac Sim, Unreal Engine), and perform sim-to-real transfer on robotic avatar and manipulators.
• Accelerate deployment of scalable robotics solutions by designing robust systems and workflows that bridge research prototypes with production-ready implementations.
• Design, execute, and evaluate demonstrations of robotic capabilities that emphasize real-world usability, autonomy, and collaborative human-robot interaction.
• Conduct thorough data analysis to validate experimental results and iterate on model and system performance across diverse environments.
• Implementing the algorithms in simulation and verify on robot hardware.
• Deliver results in accordance with the project timelines.
• Assist with compiling written and oral reports for executives within the company and run demos.
• Contribute to the portfolio of patents, academic publications, and prototypes to demonstrate research value.
• Collaborate with our teams of scientists and engineers in Honda’s regional and global R&D offices, as well as with our partners in academia and industry.
• Mentor and supervise interns or junior team members, providing guidance on both research direction and technical implementation.

Minimum Qualifications

• Ph.D. in robotics, mechanical engineering, electrical engineering, computer science, or a related field.
• Postdoctoral or industry research experience developing and deploying robotic systems using machine learning techniques such as reinforcement learning, imitation learning, or policy optimization.
• Proficiency in applying large models (LLMs/VLMs) to perception, planning, or manipulation tasks in robotics.
• Strong hands-on experience with robot kinematics, control, and motion planning for complex systems (e.g., mobile manipulators, humanoids).
• Demonstrated ability to deploy research algorithms from simulation to physical robot platforms.
• A track record of research contributions, evidenced by publications in top-tier conferences (e.g., IROS, ICRA, RSS, CoRL) and/or issued patents.
• Solid programming skills in C++ or Python and strong familiarity with ROS.
• Self-motivated to advance the project and deliver on time.
• Ability to work collaboratively in cross-functional, multi-cultural teams and communicate technical concepts clearly in written and oral form.