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breeding program. This requires a Ph.D. with excellent knowledge and skills in drones / UAV / UAS data collection, processing, statistical analyses, AI (machine learning, deep learning) and subsequent
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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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..) based on candidate expertise and interest. -Collection of data and keeping of detailed records of results, as well as utilizing computer programs and databases to conduct analyses. -Evaluate data, drafts
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proposal submission processes. Proven ability to build and maintain collaborative relationships with external stakeholders, industry partners, community organizations, and other research collaborators
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, QA/QC, harmonization, storage, and processing workflows across heterogeneous binational datasets for the TMDH framework. Support to develop APIs, dashboards, and decision-support tools (e.g., web-based
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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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utilize computational systems and applicable software, including breeding databases, perform statistical analysis, present data, and perform other computer-related tasks. Excellent written and oral
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assessment and evaluation of natural resource planning and management processes. Ability to select and conduct statistical analysis to describe spatial and temporal trends in water quality as a result of
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an international team. -Ability to multi-task and work cooperatively with others. -Ability to utilize a computer and applicable software to create databases, perform statistical analyses, present data and perform
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or equipment used to perform the essential duties of this position: computer 20 hours, telephone 5 hours, calculator 1 hour. Why Work at Texas A&M AgriLife? When you choose to work for Texas A&M AgriLife, you