Tenure-Track Professor, AI in Medicine — Genomics & Imaging

University of Pennsylvania Perelman School of Medicine

Philadelphia (Philadelphia County)

In loco

USD 180.000 - 320.000

Tempo pieno

14 giorni+

Una candidatura completa in un minuto

Curriculum e lettera di presentazione personalizzati, pronti da inviare.

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Vantaggi offerti da questo lavoro

Generous recruitment package
Lab space provided
Core facilities access

Descrizione del lavoro

University of Pennsylvania Perelman School of Medicine invites applications for an Associate or Full Professor in the tenure track in the Department of Pathology and Laboratory Medicine. The position focuses on Artificial Intelligence in Medicine, with affiliation to CHOP's Center for Computational and Genomic Medicine and a commitment to innovative research, teaching, and mentorship.

Ideal candidates will have an MD and/or PhD or equivalent, with an established independent funding record and a

Competenze

  • Candidates must hold an MD and/or PhD or equivalent.
  • Demonstrated experience in AI in medicine and leading an independent research program.
  • Strong record of teaching, mentoring, and collaboration across disciplines.

Mansioni

  • Lead an independent, externally funded research program in AI in Medicine.
  • Contribute to graduate and medical student teaching and mentoring.
  • Collaborate across CHOP, UPenn departments, and core facilities to advance precision medicine.

Conoscenze

M.D./Ph.D./equivalent
Interdisciplinary collaboration
AI in medicine

Formazione

MD/PhD or equivalent

Strumenti

AI in Medicine research
Genomics
Biomolecule design

Descrizione del lavoro

University of Pennsylvania Perelman School of Medicine invites applications for an Associate or Full Professor in the tenure track in the Department of Pathology and Laboratory Medicine. The position focuses on Artificial Intelligence in Medicine, with affiliation to CHOP's Center for Computational and Genomic Medicine and a commitment to innovative research, teaching, and mentorship.

Ideal candidates will have an MD and/or PhD or equivalent, with an established independent funding record and a

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