Research Associate - Causal

The Chronicle Of Higher Education, Inc.; Pennsylvania; On-site; USD 85,000 - 120,000; Full time

Job summary

University of Pennsylvania seeks candidates for Research Associate – Causal in the Department of Biostatistics and Epidemiology. The appointment begins with a one-year term, with renewal possible based on performance and funding. A Ph.D.

or equivalent is required and the work includes developing causal inference methods for diverse health data. Responsibilities include building statistical and ML approaches for EHRs, claims, and biobank datasets, maintaining open access software, and

Qualifications

• Ph.D. or equivalent degree required.

Responsibilities

• Develop and apply statistical and machine learning methods for analyzing EHRs, claims data, and biobank data.
• Support development and documentation of open access software implementing causal inference methods.
• Collaborate on translational biomedical research with Penn researchers and trainees.

Skills

Statistical methods

Machine learning

EHR data analysis

Claims data analysis

Biobank data analysis

Education

Ph.D. or equivalent degree

Job description

Research Associate – Causal

Location: Philadelphia, PA

Open Date: Apr 09, 2026

Deadline: Apr 09, 2028 at 11:59 PM Eastern Time

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) development and application of statistical and machine learning methods for analyzing electronic health records (EHRs) data, claims data, and biobank data; (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; and (3) collaboration on cutting-edge translational biomedical research with CCI trainees and other researchers working with the Penn School of Medicine and Children