Assistant Professor (Ophthalmology Research Track)

About the role

Location: Philadelphia, PA. Open Date: Mar 24, 2026. Deadline: Mar 24, 2028 at 11:59 PM Eastern Time. 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.

Responsibilities

• 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.

Qualifications

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