Research Assistant Professor of Epidemiology

University of Pennsylvania; United (PA); On-site; USD 110,000 - 150,000; Full time

Job summary

University of Pennsylvania in Philadelphia seeks a Research Assistant Professor of Epidemiology in the non-tenure research track to advance causal inference and machine learning methods. A Ph.D.

or equivalent is required, with a strong record of peer-reviewed publications in related fields. The successful candidate will contribute to statistical programming (R, Python, SAS), reproducible research pipelines, and multi-site collaborations with Penn faculty and external partners.

Qualifications

• Ph.D. required in Biostatistics, Statistics, Epidemiologic Methods, or closely related field.
• Experience with causal inference and machine learning methods is required.
• Demonstrated record of first- or senior-authored peer-reviewed publications in related fields.

Responsibilities

• Lead development of causal inference methodologies for observational and experimental data.
• Publish high-impact research in biostatistics, epidemiology, and clinical research journals.
• Support grant submissions (e.g., NIH, PCORI, foundations) and multi-site collaborative projects.
• Mentor graduate students, postdocs, and junior investigators, and collaborate with clinician-scientists.

Skills

Causal inference

Machine learning

Biostatistics

Epidemiology

Education

Ph.D. or equivalent degree

Tools

R

Python

SAS

GitHub

Overleaf/LaTeX

Job description

Research Assistant Professor of Epidemiology

Location: Philadelphia, PA

Open Date: Sep 25, 2026

Deadline: Sep 25, 2028 at 11:59 PM Eastern Time

The Department of Biostatistics, Epidemiology, and Informatics at the Perelman School of Medicine at the University of Pennsylvania seeks candidates for several Assistant Professor positions in the non-tenure research track. Expertise is required in the specific area of causal inference and machine learning methods. Applicants must have a Ph.D. or equivalent degree.

Research or scholarship responsibilities may include expertise in statistical programming (R, Python, SAS) and proficiency in analyzing and interpreting health outcomes, along with a demonstrated aptitude for working with state-of-the-art computing infrastructure, Overleaf/LaTeX, GitHub, and reproducible research pipelines. The successful candidate will bring a demonstrated record of first- or senior-authored peer-reviewed publications in statistical methodology, causal inference, biostatistics, epidemiology, or related fields, as well as experience developing and evaluating novel statistical methods for observational and experimental data. The candidate should demonstrate the ability to lead peer-reviewed publications in causal inference methodology applied to perinatal health and support multi-site collaborative research projects, while effectively communicating complex quantitative methods to interdisciplinary scientific audiences. Additionally, experience in collaborating with clinician-scientists, mentoring graduate students, postdoctoral fellows, or junior investigators, and contributing to federal and foundation grant submissions (e.g., NIH, PCORI, foundations) is highly valued.

The Center for Causal Inference (CCI) and the Center for Health Innovations in Reproductive and Perinatal Population Research (CHIRP) in the Division of Epidemiology, Department of Biostatistics, Epidemiology, and Informatics seeks candidates with a Ph.D. in Biostatistics, Statistics, Epidemiologic Methods, or a closely related quantitative field, with 1+ years of postdoctoral experience. The ideal candidates will be outstanding early-career researchers who will advance innovative causal inference methodologies and lead cutting-edge research in the development of novel causal inference and machine learning methods. This faculty member will be expected to lead and publish high-impact research in top-tier biostatistics, epidemiology, and clinical research journals; support, prepare, and submit grant applications; and support ongoing research studies with Penn faculty and external partners. We will begin reviewing applications on November 15th, 2026, and the position start date is flexible.

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.