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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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, 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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cotton fiber structure affects coloration. You will engage with a multidisciplinary team spanning chemistry, plant science, textile technology, engineering, and data science. This team is dedicated to improving
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protein expression and purification, biochemical screening assay development, computational structural modeling, cell-based antiviral validation studies, and exposure to preclinical small-animal research
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experience developing and evaluating reproducible geospatial analysis methods using platforms such as Google Earth Engine and GIS, comparing multi-sensor indicators, creating maps of pre-fire vegetation
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USDA-ARS Postdoctoral Research Opportunity: Development of Novel Vaccines for Poultry Viral Diseases
gain proficiency in using advanced recombineering technologies to modify cloned virus genomes, learning how to apply genetic engineering techniques for the study and manipulation of viral pathogens
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-Spectrometry, and Protein Engineering Research is available within the Food Processing and Sensory Quality (FPSQ) Unit in New Orleans, LA. The research will focus on protein chemistry and mass-spectrometry
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research that is responsive to Department of Defense and U.S. Army requirements and delivers lifesaving products including knowledge, technology and medical material that sustain the combat effectiveness
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fields (e.g. Molecular Biology, Plant Biology, Biochemistry, Microbiology, Agronomy, or closely related field). Preferred skills: Experience with DNA extractions and PCR technology. Experience in a
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to model fungal population shifts and identify environmental or biological drivers of mycotoxin risk. Collaborating with plant pathologists, microbiologists, chemists, and data scientists to develop