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among guests with food insecurity and hypertension. This is a longitudinal, prospective natural experiment with a mixed-methods RE-AIM process evaluation, conducted with community partners in the Fort
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of hydrologic processes, transboundary/shared water resources management, and coupled human–natural systems. Proficiency in geospatial and scientific computing tools (e.g., Python, R, GIS, Google Earth Engine
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emissions modeling for a local concentrated animal feeding operation (CAFO), and prepare results for publication. Collaborate with USDA‑ARS workgroup contributing to enhancements of the USEPA CMAQ/STAGE model
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. Required Qualifications: Ph.D degree in agricultural science, engineering, environmental science, hydrology, water management, or a closely related field. Preferred Qualifications: Past experience in data
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AI or machine learning applications. Formal training or professional experience in audio engineering, recording arts, or signal processing. Experience with acoustic software platforms (e.g., Pro Tools
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Agriculture (CEA) Engineering Lab as a Postdoctoral Research Associate. The candidate will primarily work in one or more of the following areas: computer vision, AI-driven automation, and/or robotics