The Stanford University School of Medicine (SoM) is recruiting multiple faculty at the Assistant, Associate, or Full Professor in the University Tenure Line (UTL), University Medical Line (UML), or Non-Tenure Line-Research (NTL-R) through this AI (Artificial Intelligence) Faculty Cluster Hire Search. We are specifically interested in candidates who have experience developing and applying novel biomedical AI and data science methods that incorporate biomedical domain expertise to ensure relevance and impact to health and medicine. Candidates will be hired into one or more SoM department(s) and contribute to the research, educational, and if relevant, clinical activities.
This AI Faculty Cluster Hire Search aims to recruit a diverse group of experts dedicated to fostering growth of biomedical AI and data science both within our organization and beyond. These distinguished individuals will become integral members of a dynamic community, collaborating not only within their respective departments or institutes but also across the SoM and our university at large.
The predominant criterion for appointment in the University Tenure Line is a major commitment to research and teaching.
The major criteria for appointment for faculty in the University Medical Line 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 line and rank will be determined by qualifications and experience. The successful candidate must have an MD, MD/PhD, or PhD with substantial expertise in one or more aspects of biomedical data science enabled or enhanced by AI. The successful candidate will be expected to develop an independent research program that advances AI approaches to biomedical data science, with a focus on their use in basic, translational, clinical, and/or population sciences.
Examples of focus areas in basic science research include development of methods to determine molecular structures, accelerate development of novel therapeutics, elucidate stem cell biology, or enable regenerative medicine. Examples of focus areas in clinical research include the development of AI methods for integration and analysis of multimodal patient data, including laboratory tests, clinical notes, images and video across multiple scales, speech to text, physiologic assays, and functional evaluations. Clinical AI research domains span across medical specialties, including but not limited to cancer, neurology, neuroscience, cardiovascular disease, intensive care, mental health, peri-operative care, pain management, ophthalmology, pediatrics, radiology, pathology, and surgery. Examples of focus areas in population health research include pharmacoepidemiology, genetic epidemiology, environmental epidemiology, AI health policy, fairness, and the legal, regulatory, ethical, and economic considerations that underlie the responsible implementation of clinical decision support tools. Research in all of these areas will benefit from broad interactions and collaborations throughout the SoM, across Stanford University, and within the large and growing health systems of Stanford Medicine.
The successful candidate will be expected to teach students, residents, postdoctoral fellows and clinical fellows, and participate in relevant clinical and basic science conferences. They will have demonstrated the potential to achieve, or have a demonstrated record of achievement in relevant rigorous research. The Departments, School of Medicine, and Stanford University value faculty who will help foster an inclusive academic environment for colleagues, students, and staff with a wide range of backgrounds, identities, and outlooks. Candidates may choose to include as part of their research and teaching statements a brief discussion about how their work and experience will further these ideals. Additional information about Stanford's IDEAL initiative may be found here: ideal.stanford.edu/about-ideal.
Review of complete applications will begin on September 23, 2024, and will continue until the positions are filled.
Interested candidates should submit the following to: facultypositions.stanford.edu/cw/en-us/job/494741/.
1. A detailed letter of research and teaching interest and if relevant, clinical specialty,
2. A curriculum vitae,
3. Three names of referees for letters of recommendation.
This role is open to candidates from multiple disciplines/specialties. The pay offered to the selected candidate will be based on their field or discipline. The expected base pay range for likely disciplines are listed below. Interested candidates whose discipline is not listed below may contact the hiring department for the salary range specific to their discipline/specialty.
PhD, Basic Science
Assistant: $185k - $203k
Associate: $218k - $242k
Professor: $266k - $296k
PhD, Data Science or related field
Assistant: $215k - $242k
Associate: $258k - $285k
Professor: $307k - $332k
MD, Research-Only (see below for further clarification)
Assistant: $190k - $208k
Associate: $218k - $242k
Professor: $261k - $279k
This pay range reflects base pay, which is based on faculty rank and years in rank. It may not include all components of faculty compensation or pay from participation in departmental incentive compensation programs. These scales do not include compensation for clinical practice, which may be relevant to specific candidates and departments. For more information about compensation and our wide-range of benefits, including housing assistance, please contact the hiring department.
Stanford University has provided a pay range representing its good faith estimate of what the university reasonably expects to pay for the position. The pay offered to the selected candidate will be determined based on factors including (but not limited to) the experience and qualifications of the selected candidate including equivalent years in rank, training, and field or discipline; internal equity; and external market pay for comparable jobs.
Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Stanford also welcomes applications from others who would bring additional dimensions to the University’s research, teaching and clinical missions.
Curt Langlotz, Professor of Radiology
Natalie Pageler, Clinical Professor of Pediatrics
Nima Aghaeepour, Associate Professor Anesthesiology, Perioperative and Pain Medicine
Olivier Gevaert, Associate Professor of Medicine
Search Committee Co-Chairs
Stanford University School of Medicine
For questions or issues with filling out the application, please contact bscacademicaffairs@stanford.edu.Please note, this inbox cannot answer questions regarding application status.
facultypositions.stanford.edu/cw/en-us/job/494741/