Research Intern: Multi-Agent Coordination & Optimal Transport

Honda Research Institute USA; San Jose (CA); On-site; USD 28,000 - 41,000; Part time

Job summary

Honda Research Institute USA in San Jose, CA invites a research intern to study the mathematical foundations of human-robot collaboration, with emphasis on optimal transport and distribution-based models of agent behavior.

The role combines mathematical analysis, algorithm development, and computational experiments to understand coordination in human-robot and multi-agent systems. Strong Python skills and a Ph.D. focus are required.

Qualifications

• Ph.D. candidate in Computer Science, Robotics, Applied Mathematics, Electrical Engineering, Statistics, OR related field.

Responsibilities

• Develop and analyze mathematical models for coordination benefits in multi-agent systems.
• Apply optimal transport to joint distributions over agent behaviors.
• Investigate how task structure affects coordination and interaction geometry.
• Develop theoretical results and computational experiments for coordination metrics.
• Implement algorithms in Python using numerical optimization and scientific computing tools.
• Design simulation experiments to validate predictions and extend to human-robot settings.
• Contribute to research publications and presentations.

Skills

Python

Mathematics

Optimization

Probability

Independent research

Education

Ph.D. student or Ph.D. candidate in a related field

Tools

CVXPY

SciPy

Job description

Honda Research Institute USA in San Jose, CA invites a research intern to study the mathematical foundations of human-robot collaboration, with emphasis on optimal transport and distribution-based models of agent behavior.

The role combines mathematical analysis, algorithm development, and computational experiments to understand coordination in human-robot and multi-agent systems. Strong Python skills and a Ph.D. focus are required.