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, or unsupervised learning methods. Proficiency in Python and familiarity with scientific computing libraries such as PyTorch, TensorFlow, Pandas, NumPy, and related ML frameworks. Experience with large datasets
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writing multiple peer-reviewed publications that disseminate research results. Mentor: The mentors for this opportunity are Jennifer Costanza (jennifer.costanza@usda.gov ), Frank Koch (frank.h.koch@usda.gov
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scientists cooperating across multiple Research Stations, the project team includes co-investigators and experts from the following collaborating organizations: Ecological Restoration Institute, Northern
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, streamflow, stream chemical exports, forest composition) at the Coweeta Hydrologic Laboratory to assess trends and variability in water yield and chemistry as affected by multiple underlying drivers. Analyses