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mission support personnel to learn the full OHS surveying process, gaining experience with equipment calibration, field study and collection, analysis requisitions, and report writing. You will participate
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at the intersection of virology, data science, ecology, and agriculture. Learning Objectives: Under the guidance of a mentor, the participant will have the opportunity to: Participate in laboratory or computational
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agricultural land to exit dairy production thereby opening opportunities for alternative agricultural enterprises. Learning Objectives: The fellow will gain experience in planning and conducting data collection
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findings will be encouraged and supported. Learning Objectives: The fellow will have the opportunity to gain or expand skillsets over a range of computational techniques needed for modern agricultural
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for participants seeking to expand their expertise in molecular biology, virology, ecology, or bioinformatics while contributing to projects of national importance. Learning Objectives: Under the guidance of a
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related area, including meteorology, hydrometeorology, remote sensing, surface and atmospheric modeling, or related fields. Experience in machine learning techniques are highly desirable. Please see https
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techniques utilized in ForestGEO and the computer software and hardware technology currently being used. The participants will be mentored as part of a larger field team to learn the field protocols
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School (NPS) Center for Infrastructure Defense (CID) leads research that supports the continued operation of critical military and civilian infrastructure systems in the presence of failure, natural
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wildland-urban interfaces— across a wide range of climate conditions. Using machine learning methods, we will optimize the weightings of each contributing factor and identify the key drivers of wildfire risk
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that protect U.S. farmers, livestock, and food security. Learning Objectives: Under the guidance of a mentor, the participant will have the opportunity to: Develop and refine computational models to predict