School of Biological and Health Systems Engineering

The Ira A. Fulton Schools of Engineering at Arizona State University (ASU) and the School of Biological & Health Systems Engineer seek applicants for a tenure-track or tenured faculty position in Artificial Intelligence (AI)/Machine Learning (ML) in Translational Womens Health. The School of Biological and Health Systems Engineering, one of the eight Fulton Schools, houses a vibrant multidisciplinary bioengineering research community (learn more at https://research.engineering.asu.edu/). We seek applicants who can enhance our abilities in these areas as part of a community of experts. Particular areas of interest include, but are not limited to, AI/ ML in translational women's health.

We search for applicants who will contribute to our academic programs, promote transdisciplinary teaching and research, and help the university to achieve its aspirations, including enabling student success, transforming society, valuing entrepreneurship, and conducting use-inspired research. Faculty members in the Fulton Schools are expected to develop an internationally recognized and externally funded research program, adopt effective pedagogical practices in the development and delivery of undergraduate and graduate courses, advise both undergraduate and graduate student research and projects, and undertake service activities.

We seek candidates conducting clinical and translational research at the intersection of women's health and artificial intelligence, machine learning, and data science. Areas of interest include the development and application of computational approaches to improve prediction, diagnosis, monitoring, treatment selection, and clinical decision-making for conditions that uniquely or disproportionately affect women. Priority areas may include reproductive and maternal health, ovarian aging and menopause, cardiovascular and metabolic disease, brain health, and other conditions in which sex-specific biology, presentation, or treatment response remains poorly understood. We are particularly interested in researchers who leverage multimodal clinical, imaging, physiological, molecular, or longitudinal health data to develop new diagnostic and predictive approaches, digital biomarkers, remote or at-home monitoring strategies, and AI-enabled tools that can be evaluated and implemented in clinical settings. Candidates should have a substantive focus on women's health and clinical impact; development of AI and/or ML methodology without a strong connection to important clinical problems is not the primary focus of this search.

Appointment will be at the Assistant Professor, Associate Professor, or (full) Professor rank, commensurate with the candidate's experience and accomplishments, beginning August 2027.

Essential Functions

• Contribute to curriculum development.
• Deliver instruction in-person and/or online.
• Supervise honors, master's, and doctoral students.
• Conduct research publishable in top-tier journals and/or conferences in the discipline.
• Develop grant proposals for external funding as PI or co-PI.
• Participate in professional and internal service.