Learning Specialist

Adaptive AI for Human Learning and Coaching - Honda Research Institute USA Adaptive AI for Human Learning and Coaching Job Number: P25F17 Honda Research Institute USA (HRI-US) is seeking a research scientist to advance research in the area of Human-AI interaction and communication alignment for next-generation multimodal AI systems. The successful candidate will conduct original research, on developing AI systems that understand human goals, intentions, beliefs, confidence, proficiency, and sense of agency, and adapt their interaction and communication to provide personalized, confidence-building coaching for skill enhancement. San Jose, CA 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 Deep expertise in one or more of the following areas: Human learning, expertise development, skill acquisition, behavior change, or adaptive support Computational modeling of human intent, proficiency, trust, preferences, strategies, workload, decision-making, or adaptation Human-AI collaboration, human-robot interaction, multi-agent systems, or adaptive autonomous agents Bayesian inference and adaptation, reinforcement learning, probabilistic modeling, causal modeling, or computational cognitive modeling Experience developing research prototypes, interactive systems, online study platforms, simulation environments, or AI-based coaching and decision-support systems Experience with modern AI/ML methods, including deep reinforcement learning, graph neural networks, diffusion models, transformers, vision-language models, or foundation models Proficiency with relevant development tools and frameworks, such as PyTorch, TensorFlow, Hugging Face, CUDA, Docker, ROS, AWS, Git, Python, or C++ Strong publication record in leading venues such as HRI, THRI, ICRA, IROS, RSS, CoRL, AAMAS, AAAI, NeurIPS, ICML, ICLR, CHI, CogSci, or related conferences and journals Desired Start Date 8/10/2026 Position Keywords Human-AI Alignment, Goal, intention & belief modeling, Machine Learning #J-18808-Ljbffr