Key Responsibilities

• Develop AI systems that infer human goals, intentions, beliefs, confidence, proficiency, trust, preferences, strategies, workload, adaptation patterns, and sense of agency from multimodal observations and interaction history
• Develop computational models that enable AI systems to reason about human cognitive and behavioral states and predict user needs during collaborative tasks
• Design adaptive interaction, communication, and coaching strategies that align AI behavior with human goals, intentions, beliefs, confidence, proficiency, and evolving task performance
• Develop machine learning methods for adaptive human-AI collaboration using reinforcement learning, probabilistic reasoning, Bayesian inference, causal modeling, multimodal learning, and foundation models
• Develop personalized coaching and assistance strategies that improve skill acquisition, enhance user confidence, and preserve and strengthen the user's sense of agency
• Build research prototypes, simulation environments, and experimental platforms for adaptive Human-AI Alignment
• Design and conduct human-subject studies to evaluate AI understanding, adaptive interaction, user experience, collaboration effectiveness, and learning outcomes
• Collaborate with multidisciplinary researchers in AI, robotics, machine learning, computer vision, and human-AI interaction
• Publish research in leading AI, robotics, and human-AI interaction conferences and contribute to patents, technical reports, and internal research milestones

Minimum Qualifications

• Ph.D. or M.S. with substantial equivalent research experience in Robotics, Computer Science, Cognitive Science, Human-Computer Interaction, Psychology, Human Factors, Learning Sciences, Electrical Engineering, Applied Mathematics, or a related field
• Strong research background in one or more areas related to computational human behavior modeling, human–AI interaction, human–robot interaction, human learning, expertise development, trust calibration, multi-agent coordination, or adaptive decision-making
• Experience developing AI or computational models that infer or predict human intentions, beliefs, preferences, trust, proficiency, confidence, or other latent human states from multimodal or behavioral data
• Experience designing, training, and evaluating AI/ML models for human behavior understanding, adaptive support, multi-agent coordination, or human–AI collaboration
• Experience designing and conducting research studies, including human-subject experiments, simulation-based evaluations, or behavioral data analyses
• Strong programming and prototyping skills, preferably in Python, with experience using machine learning or scientific computing frameworks
• Demonstrated ability to formulate research questions, design and execute experiments, analyze results, and communicate findings clearly
• 1 - 3 years of relevant work experience.

Bonus Qualifications