Research Assistant Professor of Computer Science - Agentic AI systems for Health Behavior Intervention
Description
The School of Computer Science at the University of Oklahoma invites applications for a 12-month non-tenure track Research Assistant Professor position in Computer Science with a research focus on agentic AI systems for health behavior intervention. The successful candidate will contribute to the design, development, evaluation, and deployment of advanced AI systems that support behavior change, personalized intervention, and decision support in health-related settings.
Responsibilities
The successful candidate will be expected to:
- Conduct cutting-edge research on agentic AI systems for health behavior intervention.
- Develop intelligent, autonomous, and human-centered AI agents that support personalized health coaching, behavior change, intervention planning, and adaptive decision-making.
- Design, implement, and evaluate AI methods such as large language model agents, multi-agent systems, reinforcement learning, conversational AI, human-AI interaction, and trustworthy AI for health applications.
- Collaborate with interdisciplinary teams spanning computer science, public health, medicine, psychology, behavioral science, and related fields.
- Publish in leading journals and conferences in artificial intelligence, machine learning, digital health, health informatics, and related areas.
- Contribute to the preparation of grant proposals and help expand externally funded research programs.
- Mentor graduate and undergraduate student researchers.
- Participate in appropriate professional, academic, and service activities consistent with a research faculty appointment.
Qualifications
A Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Biomedical Informatics, Human-Computer Interaction, or a closely related field by the start date of the appointment.
- Demonstrated research expertise in one or more of the following areas: agentic AI, large language models, intelligent agents, machine learning, reinforcement learning, human-AI interaction, digital health, health informatics, or computational behavioral science.
- A record of scholarly productivity appropriate for appointment at the rank of Research Assistant Professor.
- Strong programming, system-building, and experimental evaluation skills.
- Excellent written and oral communication skills.
Preferred Qualifications
Preference will be given to candidates with:
- Experience developing AI systems for healthcare, public health, mental health, or behavior-change applications.
- Experience with real-world deployment, user studies, clinical collaborations, or community-based health intervention research.
- A strong publication record in top-tier venues.
- Experience contributing to or leading externally funded research projects.
- A demonstrated ability to work in interdisciplinary research environments.
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