Research Associate – Causal

University of Pennsylvania Perelman School of Medicine; Philadelphia (Philadelphia County); On-site; USD 75,000 - 110,000; Full time

Job summary

The Department of Biostatistics and Epidemiology at the Perelman School of Medicine, University of Pennsylvania, invites applications for several Research Associate positions in Academic Support Staff. Appointment is for one year with renewals possible subject to funding and performance. A Ph.D.

or equivalent is required and applicants should demonstrate strong research independence. Responsibilities include developing and applying statistical and machine learning methods for diverse biomedical

Qualifications

• Ph.D. or equivalent degree required.
• Experience with EHR, claims and biobank data preferred.
• Strong collaboration and communication skills.

Responsibilities

• Develop and apply statistical and ML methods for EHRs, claims, and biobank data.
• Develop, document, and support open-source software implementing causal inference methods.
• Collaborate on translational biomedical research with Penn researchers and CHOP.

Skills

Statistical methods

Machine learning

Causal inference

EHR data analysis

Education

Ph.D. or equivalent degree

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

• development and application of statistical and machine learning methods for analyzing electronic health records (EHRs) data, claims data, and biobank data;
• 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;
• 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.