FDA Artificial Intelligence and -Source Data Advanced Quality Surveillance

About the Opportunity

FDA Office of Quality Surveillance (OQS) is seeking a research fellow to develop AI‑based data science tools for drug regulation.

With the development of Artificial Intelligence and Open‑Source Data for Advanced Quality Surveillance, the OQS operates in an increasingly complex regulatory environment with exponential growth in data from regulated entities. Traditional manual data review and extraction processes are resource intensive and difficult to scale for establishment and product‑level intelligence assessments. The rapid development of new AI tools/models presents an opportunity to enhance facility assessments by leveraging AI usage in open‑source.

This project aims to develop innovative assessment capabilities using techniques such as prompt engineering, data extraction, NLP, time series analysis, web‑scraping, and traditional statistical methods, transforming OQS surveillance operations while providing educational opportunities for staff.

This fellowship offers comprehensive training in the pharmaceutical regulatory space, OQS intelligence gathering methodologies, and cloud‑based data science capabilities. During the appointment, you will gain hands‑on experience with various pharmaceutical data sources and practical exposure to model evaluation, open‑source intelligence gathering, data engineering, and organizational change management. Through this, you will develop skills in translating experimental data analytics into practical pipelines for regulatory purposes and communicating complex findings to diverse stakeholders.

Stephen Cahill and Neil Stiber.

Start Date:

Anticipated June 1, 2026 (flexible). Length: one year, may be renewed. Participation: full time. Stipend: monthly, commensurate with educational level and experience.

Open to U.S. citizens, lawful permanent residents, and foreign nationals with acceptable immigration status. Participation requires proof of health insurance and completion of a background investigation.

Bachelor's, Master's, or Doctoral degree in Chemistry, Materials Sciences, Computer, Information, and Data Sciences, Life Health and Medical Sciences, or Mathematics and Statistics, received within the last five years or currently pursuing.

• Knowledge and experience developing artificial intelligence and predictive analytics using modern statistical or machine learning techniques.
• Previous experience mining complex and large data sets.
• Combined academic background in pharmaceuticals and data science.

FDA-CDER-

5/31/2026 3:00:00 PM Eastern Time Zone

Ashley