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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 an Assistant Professor position in the tenure track. Applicants must have an M.D and/or Ph.D or equivalent degree.

Teaching responsibilities may include participating in graduate and/or medical student education; mentoring trainees at multiple career stages; presenting lectures and leading didactic sessions as appropriate.

Research or scholarship responsibilities may include establishing and maintaining an independent, extramurally funded research program.

The faculty search is in the field of Artificial Intelligence (AI) in Medicine. We are particularly interested in candidates who creatively develop and apply novel AI technologies to drive biological discoveries and medical innovations. Areas of interest include, but are not limited to: foundational AI models for genetic, multi-omic, imaging, and EHR data; multimodal AI approaches enabling precision diagnostics and therapeutics; and generative AI for biomolecule engineering and design. AI researchers who combine computational and experimental research programs are also welcome to apply.

The faculty appointment will be in the Department of Pathology and Laboratory Medicine. The position is affiliated with the Center for Computational and Genomic Medicine (CCGM) at the Children’s Hospital of Philadelphia (CHOP). CCGM, a CHOP Research Institute Center of Emphasis, is housed in the state-of-the-art Colket Translational Research Building. A generous recruitment package and lab space will be provided, together with excellent institutional and core research resources. The recruitment is part of a campus-wide initiative to promote AI innovations and research-driven precision medicine.

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.