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for wheat, barley, oat, and rye. As part of a highly collaborative, multi-disciplinary team, the selected candidate will use his/her computational biology and machine learning background to help develop tools
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about the most recent advances in machine learning and data management in agricultural research. The participant will have the opportunity to collaborate with multiple USDA ARS scientists on using machine
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, repeatable coverage of fire-prone regions. When combined with modern statistical and machine-learning approaches, these data enable robust mapping of fuels, assessment of burn severity, estimation of biomass
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wildland–urban interface zones along the U.S. West Coast. Under the guidance of a mentor, you will study and implement an ensemble machine-learning framework to enhance debris flow probability prediction
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machine learning algorithms for various research projects creating medical image automation algorithms writing combat casualty care relevant military research proposals preparing manuscripts for submission
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statistical software. Learning Objectives: Learn about the implementation of the application of machine learning methodologies in plant phenotyping and genotyping for the sugarcane molecular biology lab. Learn
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these disciplines, gain access to top scientists and state-of-the-art equipment, and gain insight into research and career opportunities. You will have the opportunity to collaborate and learn from experts
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to collaborate and learn from experts researching, developing, and testing emerging technologies in marine energy and/or blue economy. You will conduct research at both your academic institution and at an external
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postdoctoral fellow interested in learning and using contemporary functional genomics approaches (CRISPR, RNAi, transgenics, etc.) to characterize the functions of genes involved in biological development
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research in several areas. Learning activities will focus on: The development and characterization of animal models and/or microphysiological systems for viral agents. Emphasis is placed on determining