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Assistant Professor (Ophthalmology Research Track)

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Assistant Professor (Ophthalmology Research Track)

University of Pennsylvania

Assistant Professor (Ophthalmology Research Track)

Skills

Data AnalysisMachine LearningAI

7 months ago

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Important information


Contract type:

Permanent

Location:

Philadelphia, PA, USA

Work mode:

Hybrid

Published on:

7 August 2026

What they need


The Department of Ophthalmology at the Perelman School of Medicine at the University of Pennsylvania seeks outstanding candidates for a full-time Assistant Professor position in the Research Track. This position is intended for individuals with a strong commitment to independent research, with a particular focus on leveraging large-scale healthcare data to advance ophthalmic clinical research and patient care. A PhD, MD, and/or equivalent degree in epidemiology, biostatistics, data science, pharmaceutical sciences, health services research, or a related field is required. Expertise is required in pharmacoepidemiology and in artificial intelligence, machine learning methods, and in the analysis of large healthcare datasets (e.g., EHR, claims, or real-world data platforms such as TriNetX). Experience in ophthalmology or vision-related research is preferred but not required.

The selected candidate will develop and lead an innovative, externally funded research program utilizing large-scale data sources, including electronic health records (EHR), administrative health claims, and national or international research networks (e.g., TriNetX and similar platforms), to address critical questions in ophthalmology and vision science.

We Are Seeking Candidates Who Can Demonstrate

  • A strong record of peer-reviewed publications.
  • Evidence of, or strong potential for, securing independent research funding.
  • Excellent communication and collaboration skills.

Research Responsibilities May Include

  • Establish and sustain an independent, high-impact research program in ophthalmology using real-world data sources.
  • Contribute to ophthalmology research through expertise in pharmacoepidemiology, real-world evidence generation, and advanced analytics using EHR and claims data.
  • Lead and support both methodological and applied research, including the development and implementation of analyses integrating artificial intelligence and machine learning to evaluate treatment effectiveness and safety.
  • Design and conduct studies using large-scale datasets, including EHR, claims databases, registries, and federated data networks.
  • Perform and oversee programming and advanced statistical analyses using large, complex datasets.
  • Collaborate with clinical faculty, data scientists, and interdisciplinary teams across the University of Pennsylvania.
  • Contribute to manuscript preparation, publication, and dissemination of research findings in collaboration with project investigators.
  • Secure extramural funding from federal agencies (e.g., NIH), foundations, and industry.
  • Publish findings in high-impact peer-reviewed journals and present at national and international conferences.
  • Mentor and supervise master-level biostatisticians in conducting statistical analyses of large-scale ophthalmic datasets.
  • Mentor trainees, including fellows, residents, and graduate students.

The Department of Ophthalmology provides a highly collaborative and interdisciplinary environment, with access to rich clinical data resources, institutional data warehouses, and established partnerships across the University of Pennsylvania. The selected candidate will have opportunities to engage with leading programs in biomedical informatics, population health, and translational science.

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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