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within the digital twin environment Developing deep learning architectures for time-series forecasting, anomaly detection, and predictive maintenance of the physical asset Designing and training Physics
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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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aerial vehicle (UAV) imagery collection and processing, deep learning methods, and rangeland vegetation communities in Oregon and Idaho as part of an interdisciplinary team including researchers in plant
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architecture trait identification. The overall objectives of the project include: Deep understanding of plant water relations to extreme environmental stresses. Hands-on experience in measuring leaf gas exchange
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/moisture retention in soils, reducing soil compaction, attracting pollinators, etc., but the overall impact of cover crops on rootzone soil moisture availability and deep percolation is not well understood
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to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including AI and machine learning (ML), to help solve complex agricultural problems that also depend
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-guided learning activities may draw upon biomonitoring projects associated with CDC’s National Health and Nutrition Examination Survey (NHANES) and similar epidemiological studies of the U.S. population
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funds can be used effectively and on time. Research Project: This fellowship will provide an opportunity to learn alongside the Crisis Cooperative Agreement and Innovation (CCI) Team. The CCI Team manages
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communities, testing dietary and other control modalities, as part of the learning experience. This will include various culture methods, nucleic acid extraction, PCR methods, sequence analysis
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. Learning Objectives: During the fellowship, under the guidance and mentorship of the mentor and senior research staff, you will: Learn how different environmental stress and biotic factors affect tree