Professor CE Track Vice Chair of Artificial Intelligence - Children's Hospital of Philadelphia (CHOP)

Location:

Aug 26, 2027 at 11:59 PM Eastern Time

Children's Hospital of Philadelphia and the Department of Pathology and Laboratory Medicine at the Perelman School of Medicine at the University of Pennsylvania seek candidates for a Full Professor position in the non-tenure clinician educator track. Expertise is required in the specific area of large language models and machine-learning algorithms and their broad application to clinical pathology. Applicants must have an M.D. degree. MD applicants must be board certified in clinical pathology and informatics; MD applicants must additionally be eligible for a medical license in the state of Pennsylvania.

Teaching responsibilities may include developing a course for pathology residents, fellows and other learners on how various AI tools can be used to improve diagnostics, reduce administrative burdens, automate manual processes, and improve patient and provider experience.

Clinical responsibilities may include helping to direct clinical chemistry and other clinical laboratories and leading faculty and staff working on AI approaches within the department and across the institution.

Research or scholarship responsibilities may include developing new machine-learning approaches to develop novel diagnostics.

Administrative responsibilities will include working with departmental and institutional leaders to craft an AI strategy and hiring and supervising staff to effect that strategy. Leadership experience at the division chief level or above is required.

Applicants must demonstrate excellent qualifications in any specific area of clinical pathology as well as the use of large language models and machine learning approaches. A strong preference will be given to applicants with experience in using AI tools in the general area of clinical pathology.

Equal Employment Opportunity Statement

The University of Pennsylvania is an equal opportunity employer. Candidates are considered for employment without regard to race, color, sex, sexual orientation, religion, creed, national origin (including shared ancestry or ethnic characteristics), citizenship status, age, disability, veteran status or any class protected under applicable federal, state, or local law.

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