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US Food and Drug Administration

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FDA Data Science Fellowship - Bioinformatics and AI/Machine Learning U.S. Food and Drug Administration (FDA) in United States

Degree Level

Master's

Field of study

Computer Science

Funding

Monthly stipend commensurate with educational level and experience; renewal contingent on availability of funds.

Deadline

Jan 4, 2027

Country flag

Country

United States

University

US Food and Drug Administration

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Keywords

Computer Science
Data Science
Biology
Mathematics
Structural Biology
Artificial Intelligence
Computational Biology
Computational Science
Software Development
High Performance Computing
Genomic
Statistics
Bioinformatic
Transcriptomic
ML

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About this position

This fellowship is based in the U.S. Food and Drug Administration’s Center for Biologics Evaluation and Research, in the Office of Biostatistics and Pharmacovigilance in Silver Spring, Maryland. The project sits at the intersection of bioinformatics, structural biology, and AI/machine learning, with an emphasis on improving scientific computing capabilities for biological data analysis.

The fellow will work on developing novel algorithms and adapting existing tools to compute, analyze, and interpret large-scale biological and scientific datasets in high-performance computing environments. The work supports FDA’s High-performance Integrated Virtual Environment (HIVE) infrastructure and scientific computing environment, and includes applications for genomics, transcriptomics, and proteomics data.

Under mentor guidance, the participant will contribute to software and computational methods that improve performance, scalability, reliability, and security of bioinformatics and structural biology applications. The role also includes maintaining and testing applications, standardizing and automating processes, and strengthening components of the AI-focused HPC environment used for biological data research.

The research environment combines public-health regulation with advanced data science and biological computation inside a federal scientific setting. The opportunity is mentored by Luis Santana-Quintero.

Funding details

Monthly stipend commensurate with educational level and experience; renewal contingent on availability of funds.

What's required

Applicants should have received a master's or doctoral degree in Bioinformatics, Computational Biology, AI/ML, Mathematics, Computer Science, or a related field, or be currently pursuing one of these degrees with completion before the appointment start date. The degree must have been received within 5 years of the appointment start date. Applicants must be U.S. citizens, lawful permanent residents, or foreign nationals with acceptable immigration status, must provide proof of health insurance, and must be able to complete a successful background investigation; non-U.S. citizens must have resided in the United States for a total of three of the past five years for the background investigation to be completed. Preferred skills include Python and scientific/AI libraries such as PyTorch, TensorFlow, Pandas, and NumPy; R or other object-oriented programming languages; Linux and shell scripting; bioinformatics knowledge including sequence alignment, clustering, and omics analysis; structural biology knowledge including protein structure and macromolecular interactions; familiarity with AlphaFold or related protein structure prediction and molecular visualization tools; and strong analytical and communication skills.

How to apply

Scroll to the bottom of the opportunity and click APPLY. Submit an application, transcripts, a current resume/CV, and one educational or professional recommendation. If you have questions, email [email protected] and include the reference code.

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