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Research Intern: Distributional Foundations of Multi-Agent Collaboration
Job Number: P26INT-12
Honda Research Institute USA (HRI-US) is seeking a self-motivated research intern to investigate the mathematical foundations of human-robot collaboration. The intern will develop methods for quantifying when and how much multi-agent systems can benefit from coordination, with a particular focus on optimal transport and distribution-based models of agent behavior. The work will combine mathematical analysis, algorithm development, and computational experiments to study fundamental properties of coordination in human-robot and multi-agent systems.
San Jose, CA
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Key Responsibilities
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- Develop and analyze mathematical models for quantifying the benefit of coordination in multi-agent systems.
- Apply optimal transport and related optimization methods to joint distributions over agent behaviors.
- Investigate how the benefits of coordination depend on task structure, agent behavior models, and interaction geometry.
- Develop theoretical results and computational experiments characterizing properties of coordination metrics.
- Implement and evaluate algorithms in Python using numerical optimization and scientific computing tools.
- Design simulation experiments to validate theoretical predictions and explore extensions to human-robot and multi-agent settings.
- Contribute to research publications and presentations resulting from the work.
Minimum Qualifications
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- Currently pursuing a Ph.D. in Computer Science, Robotics, Applied Mathematics, Electrical Engineering, Statistics, Operations Research, or a closely related field.
- Strong mathematical background, including probability, linear algebra, and optimization.
- Experience formulating and analyzing mathematical or computational models.
- Proficiency in Python and scientific computing.
- Ability to independently develop, implement, and evaluate research ideas.
Bonus Qualifications
| Years of Work Experience Required |
0 |
| Desired Start Date |
May 2027 |
| Internship Duration |
3 Months |
| Position Keywords |
Optimal transport; human-robot collaboration; multi-agent systems; coordination; coordination benefit; probability distributions;
convex optimization; distributional optimization; information theory; mathematical modeling; decision-making; robotics;
machine learning; statistical dependence
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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)
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