Have demonstrated ability to design, develop and apply state-of-the-art Data Science, ML and/or AI methodologies to biomedical text data, imaging data, omics data and other relevant healthcare data.
Experience collaborating with biomedical research programs, clinical partners or health care systems.
Evidence of strong interdisciplinary communication skills and ability to work in multi-stakeholder environments.
Develop and sustain an independent, externally funded research program, with a strong publication record and clear trajectory toward national impact.
Have demonstrated experience with real-world clinical data modalities (e.g., EHR, imaging, wearables/remote monitoring, clinical text) and rigorous evaluation/validation practices supporting translation to clinical workflows, population health, and disease-specific applications.
Experience designing multimodal and longitudinal models (e.g., sequential prediction, multimodal fusion, graph-based learning) for diagnostic/prognostic applications.
Teaching service expectations:
Teach graduate program or undergraduate courses in biomedical informatics / data science / AI and participate in curriculum development.
Participate in departmental, college and professional services (committees, peer review, editorial/reviewer activities).
Candidates pursuing senior appointments should additionally demonstrate:
Have a record of successful independent program development and leadership.
National distinction in research, teaching or patient care, within an academic environment.
Evidence of mentorship of junior faculty and trainees; or has served as a joint mentor on interdisciplinary teams.