Open Faculty Positions

The Department of Radiology at Stanford School of Medicine is recruiting a full-time faculty member at the level of Assistant, Associate, or Full Professor to join the Integrative Biomedical Imaging Informatics at Stanford (IBIIS) Division. IBIIS faculty focus on pioneering, translating, teaching and disseminating methods in data science that integrate imaging, clinical, and -omics data to better understand the molecular mechanisms of diseases and to improve the accuracy and efficiency of clinical care. Recognizing that Artificial Intelligence (AI) techniques, which are likely to be a major focus of this effort, require large sets of integrated imaging, clinical, and outcomes data, the Stanford University School of Medicine has developed and made available a research data warehouse, which includes clinical images and linked data from the electronic medical record, to enable discovery of new relationships between imaging findings and clinical, histological, and genomic manifestations of health and disease. This availability of data is coupled with access to numerous high-performance computing environments and partnerships with hyperscalers to ensure availability of requisite infrastructure for building modern AI stacks.

Appointment will be in the University Tenure Line or University Medical Line. 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. Faculty rank and line will be determined by the qualifications and experience of the successful candidate.

The new faculty will lead an innovative research program developing, translating, benchmarking, and validating AI methods to improve the practice of radiology by characterizing, reconstructing, enhancing, segmenting, classifying and/or interpreting medical images, and linking them to other imaging (e.g., pathology, ophthalmology, -omics), clinical, biological, wearables and/or -omics data. Such integration of imaging with other clinical data could enable real-time decision support for early detection of disease, more accurate diagnosis, tailored planning of treatment, creation of new clinical care pathways, precise outcome prediction and other capabilities.  Building new AI models with advanced capabilities can assist not only the practice of radiology but also all downstream clinical subfields that rely on radiological data for precise patient characterization.

The qualified candidate will have a PhD in computer science, engineering, physics, biomedical informatics, data science, imaging science, or another related field, or/and MD in any Radiology clinical specialty. We are particularly interested in candidates who have demonstrated expertise in AI, machine learning and other data science approaches that improve the practice of radiology for some or all of the following: (a) detection of disease and classification of patient data in near real-time, (b) reconstruction, de-noising, and/or otherwise enhancing images, (c) analyzing massive data sets containing both images and non-imaging data sources, (d) creating systems that employ image data to assist human decision makers, (e) developing data resources and tools that catalyze discovery, (f) rigorously validating AI models pre- and post-deployment to ensure high performance and health equity, (g) using and building upon frontier language models and agentic systems to improve patient care, and (h) implementing AI models in clinical settings and adapting to observed failure or success modes. 

The ideal candidate will have completed a postdoctoral fellowship (or/and clinical fellowship) and have (1) significant research experience resulting in high impact publications (in healthcare and AI venues) and success with grant funding (e.g., an NIH K or R grant, ARPA-H contracts) or show potential to achieve, (2) experience in developing and translating algorithms and/or methods into practical settings, and (3) the desire to seek translational collaborations with a broad range of investigators pursuing similar research goals inside and outside of Stanford. We seek motivated individuals who are committed not only to excellence in research, but also to mentoring and training the next generation of basic science and clinical researchers.  

Please apply online by submitting your curriculum vitae and a candidate statement (no longer than 3 pages) describing your research, and teaching activities and interests. The university’s central functions of research and education depend on freedom of thought, and expression. The Department of Radiology, School of Medicine, and Stanford University value faculty who will help foster an open and respectful academic environment for colleagues, students, and staff with a wide range of backgrounds, identities, and perspectives. 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 values.

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.

Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities. Applicants requiring a reasonable accommodation for any part of the application or hiring process should contact disability.access@stanford.edu.

 Salary Range:

The expected base pay range for this position (non-clinical role) is:

Assistant Professor: $234,000 - $263,000
Associate Professor: $281,000 - $308,000
Professor: $334,000 - $409,000

The expected base pay range for this position (with diagnostic radiology clinical role) is:

Assistant Professor: $453,000 - $471,000
Associate Professor: $486,000 - $504,000
Professor: $524,000 - $551,000

This pay range reflects base pay, which is based on faculty rank and years in rank. It does not include all components of the School of Medicine’s faculty compensation program or pay from participation in departmental incentive compensation programs. 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 upon hire. 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.

Please reach out to Stanford Radiology Faculty Affairs with any questions at radfacultyaffairs@stanford.edu.