The Stanford-Surgery Policy Improvement Research & Education (S-SPIRE) Center in the Department of Surgery at Stanford University seeks a candidate with expertise in developing and implementing research initiatives that leverage AI techniques to enhance surgical decision-making, improve patient outcomes, and/or advance translational surgical research to join the Department as Assistant Professor, Associate Professor, or Professor in the University Medical Line (UML), University Tenure Line (UTL), Non-Tenure Line (Research) (NTL-R). We are particularly interested in candidates who have experience and interest to collaborate with multidisciplinary teams including surgeons, data scientists, and researchers, and to contribute to the academic mission of the department through research, teaching and mentorship. Ph.D. in AI-related Data Science, Computer Science, Biomedical Engineering, or a related field is required for applicants to the UTL and NTL-R lines. Applicants to the UML position should have an MD/DO or its equivalent and be board-certified in a clinical specialty.

• The predominant criterion for appointment in the University Tenure Line (UTL) is a major commitment to research and teaching.
• The major criteria for appointment for faculty in the University Medical Line (UML) shall be excellence in the overall mix of clinical care, clinical teaching, scholarly activity that advances clinical medicine, and institutional service appropriate to the programmatic need the individual is expected to fulfill.
• The major criterion for appointment for faculty in the Non-tenure Line (Research) is evidence of high-level performance as a researcher for whose special knowledge a programmatic need exists.

Faculty rank and line will be determined by the qualifications and experience of the successful candidate.

Interested candidates should submit their curriculum vitae, a brief letter outlining their interests, and the names of three references (who will NOT be contacted without prior approval) to the "Apply Now" button.