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US Food and Drug Administration

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FDA Research Opportunity: Assessment of Bayesian Statistical Methods Applied in Regulatory Contexts U.S. Food and Drug Administration (FDA) in United States

Degree Level

Master's

Field of study

Mathematics

Funding

Monthly stipend commensurate with educational level and experience; appointment initially for one year and renewable subject to recommendation and availability of funds.

Deadline

Sep 30, 2027

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Country

United States

University

US Food and Drug Administration

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Keywords

Mathematics
Medical Science
Salud Pública
Bayesian Statistics
Regulatory Science
Trial Design
Methodologie

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About this position

U.S. Food and Drug Administration (Center for Devices and Radiological Health) is offering a research opportunity in Silver Spring, Maryland focused on assessment of Bayesian statistical methods applied in regulatory contexts. The project sits within FDA’s regulatory science environment and is tied to the agency’s mission to support safe, effective, and high-quality medical devices through science-based decision-making.

The participant will work on a multi-part research effort centered on how Bayesian methods are used, evaluated, and potentially improved for medical device regulation. Core activities include surveying Bayesian designs used in device approvals, reviewing guidance and stakeholder commentaries, and conducting literature reviews to identify novel methods with regulatory utility. The project also includes simulation-based methodological evaluation of approaches such as Bayes factors and Calibrated Bayes, as well as the study of prior-data conflict and potential mitigation strategies like adaptive borrowing or discounting.

Another major component is the evaluation of interim decision metrics. The participant will examine uncertainty and operating characteristics of PPoS-based interim decision rules across different endpoint types, including binary, continuous, and time-to-event settings, under varying modeling assumptions and data-borrowing strategies.

The opportunity is guided by mentor Rajesh Nair within the FDA CDRH environment, offering exposure to applied regulatory statistics, medical device decision-making, and high-impact methodological research.

Funding details

Monthly stipend commensurate with educational level and experience; appointment initially for one year and renewable subject to recommendation and availability of funds.

What's required

The qualified candidate should be currently pursuing or have received a master's degree in a relevant field. Preferred skills include Bayesian statistics, clinical trial design, and simulation methodology, with strong quantitative training. Applicants must provide transcripts, a current resume/CV, and one educational or professional recommendation. Documents must be in English or include an official English translation. U.S. citizens, lawful permanent residents, and eligible foreign nationals may apply; proof of health insurance is required, and a successful background investigation is necessary for onboarding at FDA.

How to apply

Apply through the Zintellect opportunity page and click APPLY at the bottom of the listing. Submit the application form, transcripts, a current resume/CV, and one recommendation. For questions, email [email protected] and include the reference code FDA-CDRH-2026-0021.

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