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in preharvest and post-harvest production and processing. This project will focus primarily on safety and quality inspection using spectral imaging techniques such as fluorescence, reflectance, and
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Language Processing / Large Language Models, image classification and object detection and Aided/Automated Target Recognition or other applications of interest to the Army to improve warfighting, lethality, and
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complicated and costly process for measuring DF content in foods. The goal of this project is to reduce the cost of dietary fiber analysis. The development of a simplified method for DF determination and
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losses and improve sensory, nutritional and functional quality. Appointment activities may include: Assess postharvest practices, biological processes and environmental conditions impacting the shelf life
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, Photonics, Quantum, Electrical/Mechanical Engineering, or relevant to the above technological areas and should be familiar with a few or more of the following analytical and experimental tools and processes
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(cattle and sheep). Through this process, the participant will acquire expertise in real-time pasture surveillance techniques for evaluating animal welfare (such as animal counts, weight, body temperature
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to our stakeholders. Baseline seed germination rates for the accessions are needed for many of the accessions as they are processed into the collection. Learning Objectives: The participant will learn
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invaluable hands-on experience and develop advanced skills while working closely with the Research Entomologist throughout all phases of the research process. This opportunity will allow you to learn and
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AI models. Successful candidates will be involved in all aspects of the scientific process from experimental design, data acquisition and analysis, and presentation and publication of results. Advisor
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, if you have additional questions about the application process, please email orise.ars.midwest@orau.org and include the reference code for this opportunity. Qualifications The qualified candidate should