FDA Postdoctoral Fellowship - Development of Virtual Animal Models to Simulate Animal Study Res

How to Apply
Submit your application through the online portal by clicking "APPLY" on the application page. Include the reference code FDA‑NCTR‑2026‑0005 in all correspondence.

U.S. Food and Drug Administration (FDA), National Center for Toxicological Research (NCTR), Jefferson, Arkansas.

FDA‑NCTR‑2026‑0005

• Start date:
  
  August/September 2026 (flexible)
• Length: 1 year, renewable based on funding and performance
• Participation:
  Full time
• Stipend:
  Monthly, commensurate with educational level and experience
• Citizenship: U.S. citizen, lawful permanent resident, or eligible foreign national. Non‑U.S. citizens must have total U.S. residence of at least 3 of the past 5 years.
• Health insurance:
  Proof required; no employment‑related benefits.

• Investigate large‑scale toxicological datasets (e.g., Open TG‑GATEs, Drug Matrix) to curate high‑quality animal study data.
• Research generative AI approaches to develop AnimalGAN, modeling relationships between chemical exposure and multidimensional biological responses.
• Analyze molecular representations to encode chemical information for modeling.
• Contribute to the development of advanced generative models (e.g., conditional GAN, Wasserstein GAN).
• Evaluate model performance using rigorous validation strategies, including internal testing, external benchmarking, and scenario‑based assessments.
• Investigate quantitative metrics to assess agreement between simulated and observed data.
• Collaborate with interdisciplinary teams to define applicability domain and regulatory relevance.
• Participate in application studies, including hepatotoxicity assessment and prediction of rare adverse events.
• Contribute to peer‑reviewed publications and scientific presentations.
• Collaborate with FDA scientists and external partners across toxicology, bioinformatics, and regulatory science.

• Generative AI and Deep Learning:
  Develop and evaluate GAN‑based models using Python and high‑performance computing.
• Computational Toxicology:
  Curate, integrate, and analyze large‑scale toxicological datasets.
• Quantitative Modeling and Validation:
  Apply statistical methods and validation frameworks.
• Cheminformatics:
  Generate molecular descriptors and perform chemical similarity analysis.
• Regulatory Science:
  Gain exposure to FDA frameworks supporting NAMs.
• Scientific Communication:
  Contribute to manuscripts, reports, and presentations.
• Prepare for careers in government, academia, or industry.
• Develop experience in AI‑driven safety assessment.

The qualified candidate should have or be pursuing a doctoral degree in one of the following fields (or a closely related discipline):

• Chemistry and Materials Sciences (including Analytical, Bio‑inorganic, Bio‑organic, Biophysical, General, Environmental, Inorganic, Materials, Organic, Physical, Polymer, Theoretical Chemistry)
• Computer, Information, and Data Sciences
• Earth and Geosciences
• Engineering
• Environmental and Marine Sciences
• Life Health and Medical Sciences
• Mathematics and Statistics
• Physics
• Science & Engineering‑related disciplines
• Social and Behavioral Sciences

• Doctoral degree.
• U.S. citizenship or lawful permanent residency, or eligible immigration status.
• Read and understand FDA Ethics Requirements.

August 28, 2026 3:00 PM Eastern Time Zone.

Ashley (contact email provided on the application page).

Weida Tong (weida.tong.gov)

All documents must be in English or include an official English translation. Application documents include the application form, transcripts, resume/CV, and one educational or professional recommendation.