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source

US Food and Drug Administration

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FDA Methodological Evaluation of Validation Approaches for AI/ML-Based Predictive Medical Devices for Regulatory Settings U.S. Food and Drug Administration (FDA) in United States

Degree Level

Postdoc

Field of study

Computer Science

Funding

Monthly stipend commensurate with educational level and experience; appointment initially for one year and may be renewed contingent on 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

Computer Science
Epidemiology
Biology
Mathematics
Predictive Modeling
Artificial Intelligence
Medical Science
Salud Pública
Regulatory Science
Statistics
Methodologie
ML

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About this position

This research opportunity at the U.S. Food and Drug Administration’s Center for Devices and Radiological Health (CDRH) focuses on the methodological evaluation of validation approaches for AI/ML-based predictive medical devices in regulatory settings.

The project centers on structured landscape analysis of device submissions, including 510(k), De Novo, and PMA SSEDs, to characterize predictive and prognostic claims, clinical study designs, performance metrics, validation strategies, and statistical methodologies. The work also includes designing and running simulation studies to compare alternative validation approaches across different data, model, and clinical scenarios, with attention to methodological gaps and robustness considerations.

The selected participant will work within a regulatory science environment at CDRH, engaging with multidisciplinary mentors and collaborators with experience in regulatory science, statistics, epidemiology, and AI/ML. The opportunity is aimed at building practical insight into how evidence is assessed for the safety and effectiveness of AI/ML-enabled medical devices and how evolving validation frameworks support regulatory decision-making.

The fellowship is embedded in FDA’s broader mission to protect and promote public health and to support medical device innovation through predictable, consistent, transparent, and efficient regulatory pathways.

Funding details

Monthly stipend commensurate with educational level and experience; appointment initially for one year and may be renewed contingent on availability of funds.

What's required

The qualified candidate should be currently pursuing or have received a doctoral degree in a relevant field. Applicants must submit an application, transcripts, a current resume/CV including academic history, employment history, relevant experience, and publication list, and one educational or professional recommendation. All documents must be in English or include an official English translation. Citizenship requirements allow U.S. citizens, Lawful Permanent Residents, and foreign nationals, and non-U.S. citizens must meet the program’s acceptable immigration status requirements. Proof of health insurance is required, and a successful background investigation by the Office of Personnel Management is required; OPM can complete this only for individuals who have resided in the U.S. for a total of three of the past five years.

How to apply

Apply through the Zintellect opportunity page and click APPLY at the bottom of the posting. Upload the required transcripts, resume/CV, and one recommendation. If you have questions, email [email protected] and include the reference code FDA-CDRH-2026-0022.

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