Research Associate – Causal

University of Pennsylvania Perelman School of Medicine; Philadelphia (Philadelphia County); On-site; USD 100,000 - 130,000; Full time

Job summary

The University of Pennsylvania Perelman School of Medicine seeks Research Associates for the Department of Biostatistics, Epidemiology and Informatics. This Academic Support Staff appointment initially runs for one year with possible renewal based on performance and funding.

Responsibilities include developing and applying statistical and machine‑learning methods to analyze EHRs, claims, and biobank data; documenting software and providing technical support for open access tools implementing

Qualifications

• Ph.D. or equivalent degree required.
• Development and application of statistical and machine learning methods for analyzing EHRs, claims data, and biobank data.
• Experience with causal inference methods and open access software is desirable.

Responsibilities

• Develop and apply statistical and ML methods for EHR/claims/biobank data.
• Document and support industry-grade open access software implementing causal inference methods.
• Collaborate on translational biomedical research with CCI trainees and other researchers.

Skills

Statistical methods

Machine learning

Causal inference

Software development

Collaboration

Documentation

Education

Ph.D. or equivalent degree

Tools

R

Python

Big data tools

Job description

University of Pennsylvania: Perelman School of Medicine: Perelman School of Medicine - Department of Biostatistics, Epidemiology and Informatics

Location

Philadelphia, PA

Open Date

Apr 09, 2026

Deadline

Apr 09, 2028 at 11:59 PM Eastern Time

Description

The Department of Biostatistics and Epidemiology at the Perelman School of Medicine at the University of Pennsylvania seeks candidates for several Research Associate positions in the Academic Support Staff. This appointment will be initially for one (1) year and continuation during that time period and renewal are based on satisfactory performance and availability of funding (limited to three (3) years). Applicants must have a Ph.D. or equivalent degree.

Responsibilities may include :

1. (1) development and application of statistical and machine learning methods for analyzing electronic health records (EHRs) data, claims data, and biobank data;
2. (2) manage the development and documentation and technical support of industry grade open access software implementing state-of-the-art causal inference methods developed by researchers at the Penn Center for Causal Inference;
3. (3) collaboration on cutting-edge translational biomedical research with CCI trainees and other researchers working with the Penn School of Medicine and Children's Hospital of Philadelphia.

The successful applicant will have an opportunity to work under the supervision of PI Dr. Eric Tchetgen Tchetgen, with a focus on methodological developments for Causal Inference and related Missing Data Problems. The candidate is expected to build a clear path towards an independent researcher in preparation for the next stage of their career.