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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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, proteomic, transcriptomic, imaging, biochemical and/or physiological experiments to elucidate factors critical for important insect traits (digestion, feeding, development, reproduction, DNA repair, etc
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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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duties as assigned. Required Qualfications: • Ph.D. in Soil Science, Agronomy, Agricultural Engineering, Geosciences, Environmental Sciences, or a closely related discipline. • Strong background in data
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and the Texas A&M Engineering Extension Service, on a state-funded project to determine the impact of manure and biosolid applications on soil health outcomes in Texas. Responsibilities: Leads a state
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communications, public health, social sciences, life sciences, engineering, data and computation science, and economics. Healthy Living implements, evaluates, and disseminates scientific solutions, applicable
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molecular genetics, genome engineering, insect genetics, DNA repair, vector biology, or a related area relevant to the position. Preferred Education: -Ph.D. with dissertation or postdoctoral research focused
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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