Key Responsibilities

• ​Conduct original research on human behavior modeling, including how cognitive, social, emotional, and physical aspects of human behavior can be represented and inferred by AI systems.
• Develop methods that enable AI agents to reason about human goals, intentions, preferences, uncertainty, and changing context during interaction.
• Design approaches for building AI systems that can reflect on the reliability of their human models, update them over time, and adapt when observations or feedback suggest the model is incomplete.
• Investigate interpretable mechanisms for analyzing model behavior, such as probing, representation analysis, causal intervention, activation analysis, or related techniques.
• Build and evaluate research prototypes that support human-aware reasoning in domains such as interactive assistants, robotics, mobility, augmented reality, decision support, or other real-world AI systems.
• Develop evaluation benchmarks, experimental frameworks, and analysis pipelines for studying human-aware AI behavior.
• Collaborate with multidisciplinary teams across AI, cognitive science, HCI, robotics, and related areas.
• Contribute to publications, research prototypes, and intellectual property that demonstrate scientific and technical impact.

Minimum Qualifications

• ​Ph.D. completed by the start date in Computer Science, Cognitive Science, Neuroscience, Psychology, Linguistics, Robotics, HCI, Applied Mathematics, Physics, or a related field.
• Strong research ability demonstrated through peer-reviewed publications, research prototypes, open-source contributions, or equivalent research output.
• Solid foundation in machine learning, artificial intelligence, computational modeling, cognitive modeling, human behavior modeling, or a closely related area.
• Experience formulating research questions, designing experiments, analyzing results, and communicating findings clearly.
• Strong programming and prototyping skills, preferably in Python and modern machine learning or data analysis frameworks.
• Strong communication and collaboration skills, including interest in working across interdisciplinary research areas.

Bonus Qualifications

• ​Experience in one or more of the following areas:
  • Human behavior and partner modeling: modeling human goals, intentions, preferences, beliefs, uncertainty, social behavior, or theory of mind.
  • Interpretable machine learning: analyzing representations, model internals, reasoning behavior, failure modes, or causal mechanisms in neural systems.
  • Cognitive or computational modeling: connecting ideas from cognitive science, neuroscience, psychology, or social cognition to artificial intelligence systems.
  • Agentic systems and memory: experience with planning, reflection, self-correction, memory architectures, or adaptive reasoning frameworks.
• Publications or research contributions in relevant venues such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ACL, EMNLP, AAAI, CogSci, CHI, HRI, RSS, CoRL, ICRA, or related conferences and journals.
• Interest in building AI systems that are interpretable, human-aware, adaptive, and useful in real-world human-centered settings.