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operations professionals, national forest system staff, state foresters in the region, and contractors. The emphasis of the project will be the analysis of past restoration treatments relevant
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production and machine learning application, and basin petroleum system modeling and data analysis, depending on qualification and project availability. Stipend: The selected participant will receive a monthly
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simulations for gas production and machine learning application, and basin petroleum system modeling and data analysis, depending on qualification and project availability. Stipend: Participants receive a
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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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techniques with high-resolution mass spectrometry for the analysis of phytochemicals. Hand-on experiences on growing agricultural products in controlled environmental agriculture (CEA) Analytical method
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opportunity of the fellows will be to participate in the preparation of samples for chemical analysis and learn a range of skills associated with a chemistry laboratory. Samples may be soils, sediments, plant
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analysis of carrot nutrients and anti-nutrients, plant growth, pest and disease resistance. Activities include periodic travel to field sites within the U.S. Learning Objectives: Specific learning objectives
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data analysis skills Technical paper writing skills Poster presentation skills. Point of Contact Cinnamon Eligibility Requirements Degree: Doctoral Degree received within the last 60 months or currently
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: Human identification Detection of Bio-threat agents Detection of explosives and drugs Characterization and comparison of forensic materials Elemental analysis of trace evidence Mass spectrometry
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to: Learning about aircraft systems engineering and systems analysis to support integrated design and performance assessment. Participating in aircraft design trade studies with a focus on propulsion–airframe