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Causal Inference Phd Internship information

What types of projects does a causal inference PhD intern typically work on during their internship?

Causal Inference PhD interns often engage in projects that involve designing and analyzing experiments or observational studies to draw valid conclusions about cause-and-effect relationships. These projects might include developing statistical models, collaborating with data scientists and product teams, and presenting findings to inform business or policy decisions. Interns usually have the opportunity to work with large-scale, real-world data, and are encouraged to publish or present their work at conferences, supporting both professional growth and academic development.

What are the key skills and qualifications needed to thrive as a causal inference PhD intern, and why are they important?

To thrive as a Causal Inference PhD Intern, you need a strong background in statistics, econometrics, and causal inference methods, often supported by advanced graduate studies in a related field. Familiarity with statistical programming languages such as R or Python, and experience using data analysis tools and frameworks like Stata or TensorFlow Probability, are typically required. Excellent problem-solving abilities, critical thinking, and the ability to communicate complex concepts clearly help you stand out in this role. These skills and qualities are crucial for designing robust experiments, drawing reliable conclusions, and effectively collaborating with interdisciplinary research teams.

What is the difference between Causal Inference Phd Internship vs Data Scientist Internship?

AspectCausal Inference Phd InternshipData Scientist Internship
Required CredentialsPhD in statistics, economics, or related fieldBachelor's or Master's in CS, statistics, or related field
Work EnvironmentResearch-focused, academic or industry research teamsData analysis, modeling, and business insights
Employer & Industry UsageResearch institutions, tech companies, financeTech firms, startups, finance, healthcare
Search & Comparison IntentFocus on causal inference research rolesBroader data analysis roles

While a Causal Inference Phd Internship emphasizes research in causal analysis with advanced credentials, a Data Scientist Internship covers broader data analysis skills suitable for various industries. Both roles involve working with data, but their focus, required background, and career paths differ significantly.

What is a causal inference PhD internship?

A Causal Inference PhD Internship is a specialized research position for doctoral students focused on causal inference, which involves determining cause-and-effect relationships from data. Interns typically work with large datasets, advanced statistical models, and machine learning techniques to answer questions about how variables influence one another. These internships are often offered by tech companies, research labs, or policy organizations and provide hands-on experience in designing experiments, analyzing observational data, and developing new methodologies. The goal is to bridge academic research with real-world applications, contributing to projects that require rigorous causal analysis.
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Causal Inference Phd Internship jobs near you

Postdoctoral Associate Position in Pharmacoepidemiology, Perinatal Epidemiology, and Causal Inferenc

Yale University

New Haven, CT • On-site

Full-time

Re-posted 26 days ago

Yale University rating

8.6

Company rating: 8.6 out of 10

Based on 64 frontline employees who took The Breakroom Quiz

67th of 616 rated colleges and universities

Job description

Description
Posting date: November 15th, 2025
Title of the Position: Postdoctoral Associate
School: Yale School of Public Health
Department: Department of Environmental Health Sciences, Yale Center for Perinatal, Pediatric and Environmental Epidemiology
Anticipated Appointment Date: February 15th, 2026
Fixed Term: One year, Full-time (renewable)
The Liew lab at the Yale School of Public Health (YSPH) and the Yale Center for Perinatal, Pediatric, and Environmental Epidemiology (CPPEE) is inviting qualified individuals to apply for a Postdoctoral Associate position in the multidisciplinary fields of pharmacoepidemiology, perinatal epidemiology, and causal inference, starting on February 15th, 2026, or soon thereafter. The position is a one-year, full-time role, renewable contingent upon performance and funding. The position is supported by a Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) project. The Postdoctoral Associate will collaborate with a renowned national and international team to develop cutting-edge epidemiologic methods and investigate the heterogeneity of medication effects during pregnancy and child development. The Postdoctoral Associate will have opportunities to work with the Danish National Birth Cohort (DNBC) in Denmark, as well as with US MarketScan data and Yale electronic healthcare data. The research partners include the Yale Pharmacoepidemiology Working Group (Yale PEW) and the Practical Causal Inference (PCI) lab at UCLA.
Qualifications
Candidates should possess a PhD, preferably in epidemiology, biostatistics, and/or health data sciences. Candidates with research experience analyzing longitudinal cohort or health registry data using causal inference methods, as well as those with research interests relevant to perinatal or pharmacoepidemiology, are preferred.
The position will require extensive experience with programming languages and statistical software packages, such as R or SAS. The Postdoctoral Associate position will require excellent interpersonal skills to facilitate effective communications and collaborations across local, national, and international research teams. The Postdoctoral Associate position requires motivation to work in an inclusive team-oriented environment, strong scientific integrity, and a high level of competency in English, both in written and oral formats.
Salary will be based on the Yale Postdoctoral Compensation policy, and support for travel to conferences may also be available.
Application Instructions
Yale University will use Interfolio to search for this position. Applicants receive a free Dossier account and can send all application materials at no cost.
Please apply online.
To apply, please submit a CV, a cover letter, and contact information for three references. In the cover letter to the application package, please summarize your relevant research experience, indicate your specific research interests, and the date you will be available to start.
For questions, please contact the Yale Center for Perinatal, Pediatric and Environmental Epidemiology, Email: cppee@yale.edu

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