Research Intern: Multimodal Learning for Human-AI Teaming

Honda Ri; San Jose (CA); On-site; USD 34,000 - 55,000; Full time

Job summary

Honda Research Institute USA invites a research intern to develop multimodal fusion methods for understanding human and AI behavior in group interactions. You will explore integrating language, speech, visual signals, and interaction context through learning representations across modalities and participants.

candidates should be PhD students in CS/Robotics/Cognitive Science with a strong publication record and Python/Machine Learning framework experience.

Qualifications

• Current Ph.D. student in Computer Science, Robotics, Cognitive Science or a related field.
• Familiarity with multimodal fusion, representation learning, cross-modal alignment, foundation models, or social signal processing.
• Proficiency in Python and experience with established machine learning frameworks.
• Proven publication record in machine learning, NLP, CV, or HCI venues.

Responsibilities

• Develop multimodal fusion methods for integrating language, speech, and visual signals.
• Learn representations that capture information across modalities, participants, and time.
• Evaluate fusion approaches for conflicting or missing signals.
• Examine model generalization, interpretability, and robustness across interaction settings.
• Present research progress and contribute to publications, prototypes, or demonstrations.

Skills

multimodal fusion

representation learning

cross-modal alignment

foundation models

social signal processing

Python

Education

Ph.D. student in CS/Robotics/Cognitive Science

Job description

Honda Research Institute USA invites a research intern to develop multimodal fusion methods for understanding human and AI behavior in group interactions. You will explore integrating language, speech, visual signals, and interaction context through learning representations across modalities and participants.

candidates should be PhD students in CS/Robotics/Cognitive Science with a strong publication record and Python/Machine Learning framework experience.