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USDA-ARS Computational Biology & Machine Learning for Avian Influenza Surveillance U.S. Department of Agriculture (USDA) in United States
Degree Level
Postdoc
Field of study
Computer Science
Funding
Stipend of $74,677.00–$74,678.00 per year for a two-year full-time appointment.
Deadline
Jan 15, 2027
Country
United States
University
U.S. Department of Agriculture
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About this position
This research opportunity is with the USDA Agricultural Research Service’s Genomics and Bioinformatics Research Unit in Gainesville, Florida. The project sits at the intersection of avian influenza surveillance, computational biology, and machine learning, with a strong emphasis on building practical tools that can help diagnostics keep pace with viral evolution.
The fellowship combines two related research directions. One focuses on predicting when PCR-based diagnostics may fail as influenza viruses accumulate primer-template mismatches, using machine-learning models trained on molecular data and validated with data from federal partner laboratories. The other explores how influenza proteins may adapt to mammalian hosts through structure-based modeling of hemagglutinin and neuraminidase interactions with avian- and human-type sialic acid receptors. The work may involve AlphaFold-based modeling, glycan-aware docking or co-folding, and molecular-dynamics simulations with OpenMM and AMBER-family force fields.
The lab environment is highly interdisciplinary and software-oriented, with workflows based in Python and moving toward Rust. Fellows are encouraged to develop open-source tools and datasets, contribute to reproducible research software, and present work at conferences. The project also includes collaboration with federal animal-health research partners and interaction with the University of Florida Emerging Pathogens Institute and the Microbiology and Cell Science department.
The position is mentored by Adam Rivers, whose group builds open, reproducible bioinformatics software and supports trainees from both wet-lab and computational backgrounds. The fellowship is designed to help the student strengthen skills across biology, virology, bioinformatics, machine learning, and structural modeling while contributing to surveillance methods for a changing influenza landscape.
Funding details
Stipend of $74,677.00–$74,678.00 per year for a two-year full-time appointment.
What's required
Applicants should be currently pursuing or have received a doctoral degree in biology, molecular biology, bioinformatics, computational biology, machine learning, biophysics, or a related field. The degree must have been received within the past four years, or be anticipated by 2027-01-30. This opportunity is available to U.S. citizens only. Preferred preparation includes experience with PCR/qPCR assay design, primer design, molecular diagnostics, protein structure prediction tools such as AlphaFold or ESMFold, molecular dynamics packages such as OpenMM, GROMACS, or AMBER force fields, hands-on deep learning experience in PyTorch or TensorFlow, proficiency in Python and scripting, willingness to learn Rust, reproducible-research tooling such as git, Nextflow, containerization, and slurm, background in virology or influenza biology, and a track record of first-author publication or open-source software contribution. Applicants should also be comfortable working across computational and biological disciplines.
How to apply
Scroll to the bottom of the opportunity page and click APPLY. Submit the application, an unofficial transcript or academic record, a current resume/CV, and two educational or professional recommendations. Ensure all documents are in English or include an official English translation.
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Prepare your application
Review drafts and confirm requirements with the university.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.