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U.S. Department of Agriculture
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USDA-ARS Image Based Soil Health Analysis Postdoctoral Fellowship U.S. Department of Agriculture (USDA) in United States
Degree Level
Postdoc
Field of study
Computer Science
Funding
Stipend of $6,705.00 monthly; appointment initially for one year and may be renewed contingent on availability of funds.
Deadline
Dec 4, 2026
Country
United States
University
U.S. Department of Agriculture
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About this position
This postdoctoral fellowship is hosted by the U.S. Department of Agriculture’s Agricultural Research Service (USDA-ARS) in Corvallis, Oregon, within the Horticultural Crop Production and Genetic Improvement Research Unit. The project centers on image-based soil health analysis, combining advanced sensing and imaging technologies to study how soil health management practices influence soil health metrics, crop yield, and crop quality.
The fellow will work with a range of imaging systems, including x-ray computed tomography, RGB-D cameras, hyperspectral cameras, x-ray instruments, imaging boxes, and robot-mounted cameras. A major part of the work is high-throughput image data analysis across multiple imaging modalities, with computational workflows developed in Python and deployed across local systems, edge-computing devices, and Department of Energy and Department of Agriculture computing clusters.
The role is collaborative and interdisciplinary, involving researchers in crop production, genetics, engineering, and data science. The fellow will also contribute to manuscripts for peer-reviewed publication based on the project’s results. The opportunity includes travel to data-collection sites in Washington, California, and Illinois, including synchrotron light sources and vineyards.
The research is guided by mentor Devin Rippner at USDA-ARS.
Funding details
Stipend of $6,705.00 monthly; appointment initially for one year and may be renewed contingent on availability of funds.
What's required
Applicants must be currently pursuing or have received a doctoral degree in a relevant field. The degree must have been received within the past five years, or be anticipated by 2026-12-31. This opportunity is available to U.S. citizens only. Preferred qualifications include a strong interest in imaging technologies for soil and plant processes, experience implementing ML/DL-based image processing and analysis pipelines in Python or an equivalent language, comfort operating instrumentation in U.S. National Laboratory facilities and in vineyards, troubleshooting autonomous sensing platforms, prior peer-reviewed publication experience, and experience with x-ray computed tomography or autonomous image collection platforms.
How to apply
Submit the application through the Zintellect/ORISE portal by clicking APPLY on the opportunity page. Include transcripts, a current resume/CV, and two recommendations. Make sure all documents are in English or include official English translations.
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