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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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improving plant health using machine learning and artificial intelligence. Mentor(s): The mentor for this opportunity is Yulin Jia (yulin.jia@usda.gov ). If you have questions about the nature of the research
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machine learning, image recognition, and prediction of damage to tree nuts from insect pests. They will also collaborate with other team members on statistical analysis of data collected as part of
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and Data Science (including machine learning and AI for defense applications) - Systems Engineering and Engineering Management - Industrial Engineering and Production Management - Mathematical Modeling
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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
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-Docs, post-Bacs, summer internships, etc.) to those interested in research in the following fields: Theory and application of machine learning and artificial intelligence including Natural
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? As the selected participant, you will primarily engage in research activities with the Senior Scientist for the CFI Military Performance Laboratory; a laboratory which conducts translational research
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on the blockchain. A hands-on familiarity with machine learning and blockchain or related research is required as are Python or other coding skills. Quantum computing – This research is exploratory, applying hands
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-property relationships, statistics and probability, applied mathematics, data science, or machine learning. Application Requirements A complete application consists of: Zintellect Profile Educational and