What are the responsibilities and job description for the Adaptive and Human-Centric AI Systems position at Honda Research Institute USA?
Job Number: P24INT-48
Honda Research Institute USA (HRI-US) is seeking a driven and creative research intern to join our efforts in developing adaptive AI systems that can operate in complex, human-AI collaborative environments. This internship offers the opportunity to work on algorithms and frameworks that enable robots and agents to rapidly interpret new tasks, adapt to evolving team dynamics, and cooperate meaningfully with humans. The work will explore state-of-the-art approaches such as meta-reinforcement learning for fast task adaptation and grounded foundation models for richer language- and context-based understanding. By combining these with insights from human cognition, we aim to create agents that not only optimize performance but also support trust, empathy, and long-term collaboration.
San Jose, CA
Key Responsibilities
- Investigate and implement algorithms for fast adaptation and task generalization, with a focus on meta-reinforcement learning and related adaptive learning strategies
- Explore the use of grounded foundation models to improve contextual understanding, intention recognition, and human-AI communication in this context
- Collaborate with a multidisciplinary team of researchers to design and implement cutting-edge solutions
- Publish research findings in top-tier conferences and journals
Minimum Qualifications
- Currently enrolled as a Ph.D. student in Computer Science, Machine Learning, or a related field at a reputed university (exceptional M.S. candidates with a minimum of 1 year of research experience may also be considered
- Strong familiarity with RL, Meta-RL and modern foundation model training techniques
- Experience in open-source deep learning frameworks (PyTorch, JAX, etc.)
Bonus Qualifications
- Experience with multi-agents settings (simultion testbeds, etc.)
Years of Work Experience Required
0
Desired Start Date
1/5/2026
Internship Duration
3 Months
Position Keywords
Meta-reinforcement learning, meta-cognitive AI
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