FDA Fellowship - Mechanistic Modeling and Simulation

Oak Ridge Institute for Science and Education; White Oak (MD); On-site; USD 33,480 - 55,800; Full time

Job summary

FDA/CDER/OPQ in White Oak, Maryland offers an ORISE fellowship focused on regulatory science research. The fellow will work on AI/ML methods, mechanistic modeling, and data-driven approaches to improve pharmaceutical product quality and manufacturing processes.

Collaboration with multidisciplinary FDA teams is emphasized to develop credible modeling strategies and regulatory-ready insights. The appointment is for one year, full-time, with a monthly stipend commensurate with education and

Qualifications

• The qualified candidate should be currently pursuing or have received a master's or doctoral degree in one of the relevant fields.
• Eligibility includes U.S. citizens, Lawful Permanent Residents (LPR), and foreign nationals.

Responsibilities

• Develop AI and machine learning methods for pharmaceutical manufacturing and product quality challenges.
• Construct and evaluate mechanistic, mathematical, statistical, and hybrid models of pharmaceutical systems.
• Collaborate with FDA scientists to learn regulatory science principles and model-informed approaches.

Education

Master's degree or Doctoral Degree in relevant fields

Job description

Organization

U.S. Food and Drug Administration (FDA)

Reference Code

FDA-CDER-2026-0141

Application Deadline

9/25/2026 3:00:00 PM Eastern Time Zone

Description

• Applications will be reviewed on a rolling-basis.

FDA Office and Location

A research opportunity is available immediately with the Food and Drug Administration (FDA),Center for Drug Evaluation and Research (CDER), Office of Pharmaceutical Quality (FDA/CDER/OPQ), located in White Oak, Maryland.

The Center for Drug Evaluation and Research (CDER) performs an essential public health task by making sure that safe and effective drugs are available to improve the health of people in the United States. As part of the U.S. Food and Drug Administration (FDA), CDER regulates over-the-counter and prescription drugs, including biological therapeutics and generic drugs. This effort covers more than just medicines.

Research Project

The U.S. Food and Drug Administration’s Center for Drug Evaluation and Research, Office of Pharmaceutical Quality (FDA/CDER/OPQ), is seeking an ORISE fellow to gain experience in regulatory science research supporting pharmaceutical product quality. The project will focus on the development and application of artificial intelligence, machine learning, mechanistic modeling, mathematical modeling, and simulation methods to pharmaceutical manufacturing and product characterization.

The fellow will collaborate with and learn from multidisciplinary FDA scientists to develop data-driven and first-principles models and evaluate how they can be used to improve understanding of pharmaceutical products and manufacturing processes. The research will contribute to the development of scientific principles, evaluation strategies, and best practices for the use of computational models and AI-enabled methods in pharmaceutical quality.

Potential Research Topics Include

• Machine learning and deep learning methods for process monitoring, anomaly detection, fault diagnosis, and prediction of critical quality attributes.
• Data-driven models for process optimization, real-time release testing, and manufacturing process control.
• Mechanistic and mathematical models of pharmaceutical unit operations, transport phenomena, material behavior, and product performance.
• Hybrid modeling approaches that combine mechanistic knowledge with machine learning.
• Model calibration, validation, uncertainty quantification, sensitivity analysis, and assessment of model credibility.
• Computational characterization of pharmaceutical products using physicochemical, structural, formulation, manufacturing, and performance-related data.
• Evaluation of AI- and model-based methodologies submitted in support of pharmaceutical development, manufacturing, and quality assessment.

Learning Objectives

• Learn to develop and apply AI and machine learning methods to pharmaceutical manufacturing and product quality challenges.
• Gain experience constructing and evaluating mechanistic, mathematical, statistical, and hybrid models of pharmaceutical systems.
• Learn to analyze complex manufacturing, formulation, material, and product-performance data to support scientific and regulatory objectives.
• Develop skills in model verification, validation, uncertainty quantification, and credibility assessment methods.
• Build knowledge of regulatory science principles and FDA frameworks related to pharmaceutical quality and model-informed approaches.
• Learn to translate computational and modeling results into scientifically defensible conclusions that support regulatory assessment activities.
• Gain experience preparing technical reports, scientific manuscripts, presentations, and other research communications.
• Develop collaborative skills by working with scientists, engineers, statisticians, data scientists, and regulatory reviewers on interdisciplinary projects.

Mentor

The mentor for this opportunity is Jianan Zhao ([e-mail]). If you have questions about the nature of the research, please contact the mentor.

Anticipated Appointment Start Date

September 2026. Start date is flexible and will depend on a variety of factors.

Appointment Length

The appointment will initially be for one year, but may be renewed upon recommendation of FDA and is contingent on the availability of funds.

Level of Participation

The appointment is full time.

Participant Stipend

The participant will receive a monthly stipend commensurate with educational level and experience.

Citizenship Requirements

This opportunity is available to U.S. citizens, Lawful Permanent Residents (LPR), and foreign nationals. Non-U.S. citizen applicants should refer to the Guidelines for Non-U.S. Citizens Details page of the program website for information about the valid immigration statuses that are acceptable for program participation.

This program, administered by ORAU through its contract with the U.S. Department of Energy to manage the Oak Ridge Institute for Science and Education, was established through an interagency agreement between DOE and FDA. The participant will receive a monthly stipend commensurate with educational level and experience. Proof of health insurance is required for participation in this program. Participants do not become employees of FDA, DOE or the program administrator, and there are no employment-related benefits.

Completion of a successful background investigation by the Office of Personnel Management is required for an applicant to be on-boarded at FDA. OPM can complete a background investigation only for individuals, including non-US Citizens, who have resided in the US for a total of three of the past five years.

FDA Ethics Requirements

If an ORISE Fellow, to include their spouse and minor children, reports what is identified as a Significantly Regulated Organization (SRO) or prohibited investment fund financial interest in any amount, or a relationship with an SRO, except for spousal employment with an SRO, and the individual will not voluntarily divest the financial interest or terminate the relationship, then the individual is not placed at FDA. For additional requirements, see FDA Ethics for Nonemployee Scientists.

Education

• Non-employee nature of the ORISE appointment;
• Prohibition on ORISE Fellows performing inherently governmental functions;
• Obligation of ORISE Fellows to convey all necessary rights to the FDA regarding intellectual property conceived or first reduced to practice during their fellowship;
• The fact that research materials and laboratory notebooks are the property of the FDA;
• ORISE fellow’s obligation to protect and not to further disclose or use non-public information.

Qualifications

The qualified candidate should be currently pursuing or have received a master's or doctoral degree in the one of the relevant fields.

Point of Contact

Ashley

Eligibility Requirements

• Degree: Master's Degree or Doctoral Degree.
• Discipline(s):
  • Chemistry and Materials Sciences
    • Analytical Chemistry
    • Bio-inorganic Chemistry
    • Bio-organic Chemistry
    • Biophysical Chemistry
    • Chemistry (General)
    • Environmental Chemistry
    • Inorganic Chemistry
    • Materials Sciences
    • Organic Chemistry
    • Physical Chemistry
    • Polymer Chemistry
    • Theoretical Chemistry
  • Communications and Graphics Design (2 )
    • Computer, Information, and Data Sciences (17 )
      • Earth and Geosciences (21 )
        • Engineering (29 )
          • Environmental and Marine Sciences (14 )
            • Life Health and Medical Sciences (51 )
              • Mathematics and Statistics (11 )
                • Physics (16 )
                  • Science & Engineering-related (1 )

      Affirmation

      I am a U.S. citizen, or I have lived in the United States for at least 36 out of the past 60 months. (36 months do not have to be consecutive.) and I have read the FDA Ethics Requirements.