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state-of-the-art experimental and computational models for solving water resource problems worldwide. CHL research and development addresses water resource and navigation challenges in a variety of
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of the agency is to provide global leadership in agricultural discoveries through scientific excellence. Research Project: The Environmentally Integrated Dairy Management Research Unit (EIDMRU) within the U.S
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documenting insights that can inform Agency-wide AI governance and implementation efforts. You will apply machine learning methods and applied AI tools, including experience with large language models (LLMs
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, and environmental factors associated with diabetes incidence, prevalence, complications, and trends. Learn and apply advanced statistical and machine learning methods, including cluster analysis and
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data from December 2025 to the present to identify workload distribution patterns and refine the algorithm using mathematical modeling, programming, and integrated data systems. Project outcomes will
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or simulated data to address statistical problems in a stimulating, collaborative, and supportive environment. Past research project areas have included modeling and simulation, missing data, noninferiority
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the soil-water-plant-air continuum using process-based models. You will learn how to take proper soil, plant and air samples that influence carbon and nitrogen dynamics and learns how soil and plant
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collecting soil, plant, and water samples; monitoring soil moisture with advanced sensors; organizing and processing research data; and contributing to modeling efforts that examine water and nutrient dynamics
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analysis, secondary data analysis, or statistical modeling. Strong scientific writing skills and demonstrated ability to communicate complex findings to diverse audiences. Demonstrated ability to research
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to classify rangeland plant species, and (2) using transfer learning to adapt deep learning models for imagery analysis to varying UAV sensors and conditions. These techniques will allow you to identify and