Research Assistant Professor of Epidemiology
About The Position
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. 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 PhD 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.
Requirements
- Ph.D. or equivalent degree
- Expertise in causal inference and machine learning methods
- Demonstrated record of first- or senior-authored peer-reviewed publications in statistical methodology, causal inference, biostatistics, epidemiology, or related fields
- PhD in Biostatistics, Statistics, Epidemiologic Methods, or a closely related quantitative field
- 1+ years of postdoctoral experience
Nice To Haves
- Experience in collaborating with clinician-scientists
- Mentoring graduate students, postdoctoral fellows, or junior investigators
- Contributing to federal and foundation grant submissions (e.g., NIH, PCORI, foundations)
Responsibilities
- Expertise in statistical programming (R, Python, SAS)
- Proficiency in analyzing and interpreting health outcomes
- Demonstrated aptitude for working with state-of-the-art computing infrastructure, Overleaf/LaTeX, GitHub, and reproducible research pipelines
- Developing and evaluating novel statistical methods for observational and experimental data
- Lead peer-reviewed publications in causal inference methodology applied to perinatal health
- Support multi-site collaborative research projects
- Effectively communicating complex quantitative methods to interdisciplinary scientific audiences
- Collaborating with clinician-scientists
- Mentoring graduate students, postdoctoral fellows, or junior investigators
- Contributing to federal and foundation grant submissions (e.g., NIH, PCORI, foundations)
- Lead and publish high-impact research in top-tier biostatistics, epidemiology, and clinical research journals
- Support, prepare, and submit grant applications
- Support ongoing research studies with Penn faculty and external partners
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
Ph.D. or professional degree
