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) immunology machine learning/AI single cell profiling Point of Contact Ashley Eligibility Requirements Degree: Doctoral Degree received within the last 36 months or anticipated to be received by 5/31/2026 11:59
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plants. The participant will learn and use multiple molecular biology, synthetic biology and plant biotechnology related tools and techniques including plasmid vector design and assembly, plant genetic
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regions will be evaluated for features such as signatures of selection or diversifying or purifying selection, around genes and regions of agricultural importance. Learning Objectives: The participant will
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phenotyping using both drone-based and ground based sensing platforms. Learn artificial intelligence and machine learning techniques to analyze image and geospatial data from diverse sources for crop monitoring
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Raman imaging technologies for safety and quality evaluation of agricultural products. Learn artificial intelligence/machine learning methods to evaluate hyperspectral image data to assess safety and
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to the continent, and sub-daily to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including artificial intelligence (AI) and machine learning, to help
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and stress), behavior (grazing behavior halters, accelerometer-based ear tags, chute velocity measures), environmental monitoring, and pasture measures. Learning Objectives: Under the mentor's guidance
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, software applications, record keeping, compliance training, and the principles of scientific study design. Learning both general and specialized research skills that will support advancing your scientific
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the underlying impacts of stressors on bee health and analytical skills for understanding colony level dynamics and predicting mass colony loss events. Learning Objectives: The fellow will learn and apply
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, statistics, and field-lab approaches. Learning Objectives: The participant will receive training in plant molecular biology, genetics, and genomics. This research is expected to result in increased learning