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areas. These include, but are not limited to: Applying machine learning algorithms to solve real-world problems. Creating and structuring databases for storage, retrieval, and image analysis. Determining
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flood-induced resistance. Learning Objectives: The participant will expand their skills in plant metabolite analysis, plant genetics, and plant stress biology. They will also receive mentoring in writing
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flood-induced resistance. Learning Objectives: The participant will expand their skills in plant metabolite analysis, plant genetics, and plant stress biology. They will also receive mentoring in writing
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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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degradation that could occur to C-130 crew members from extended exposure to environmental insults. This research will also inform the development of effective human-machine systems and healthy Airmen protocol
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, the participant will learn HPC computing technologies and techniques in genomic epidemiology and machine learning to quantify drivers of IAV evolution in swine using data generated from IAV surveillance in human
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contributions are valued and your growth is encouraged. This fellowship is ideal for enthusiastic, team-oriented individuals eager to learn and make meaningful contributions to the field of emerging infectious
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instrumentation and analysis, data management, software applications, record keeping, compliance training, and the principles of scientific study design. Learning both general and specialized research skills
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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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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