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sensors, RGB/IR cameras, video systems, insect traps, and other devices to build predictive, AI- and machine-learning based models for monitoring grain quality and detecting deterioration due to mold
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Animals—and their importance for vaccination-based disease-control programs. Learn how diagnostic approaches can distinguish vaccine-induced immune responses from evidence of field-virus infection. Develop
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, implementation of management treatments, and the use of coding and process-based models to analyze natural resource dynamics. Learning Objectives: Under the guidance of a mentor, you will build experience in plant
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chromatography-based purification techniques (FPLC/AKTA). Exposure to or an enthusiastic willingness to learn—computational structural biology tools (such as AlphaFold, PyMOL, Rosetta, or basic molecular docking
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as safely and securely as possible. Learning Objectives: Under the guidance of a mentor, you will learn from DRSC’s Biosafety, Science, Training, and Expertise Branch while participating in a variety
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with analytical methods, such as spectroscopy (FT-IR, NIR, UV-Vis), microscopy, or X-ray–based techniques, with willingness to learn cotton-specific applications. Ability to interpret physical
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design with hands-on wet-lab expression, purification, and biophysical characterization. You will have the opportunity to learn and gain experience at the intersection of structural biology, AI, and
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environmental stresses will help food regulators in making science-based decisions and help in the development of more effective intervention technologies to improve food safety and shelf-life. Specific project
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USDA-ARS Postdoctoral Research Opportunity: Development of Novel Vaccines for Poultry Viral Diseases
of the agency is to provide global leadership in agricultural discoveries through scientific excellence. Research Project: You will be part of the research team learning about developing recombinant Marek's
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conducting molecular-based assays such as ddPCR and/or qPCR, and biochemical analyses via chemical extractions and collaboration with unit Chemists. Data collected from these experiments will contribute