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Field
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, or modeling using tools such as Python, R, GIS, or similar computational platforms. Demonstrated ability to collaborate across disciplines and translate technical and social science insights into scholarly
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collaborators. These deployments provide a rare opportunity to construct digital twins grounded in operational infrastructure, live data, and scalable computation. This position is not focused on conventional GIS
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, perinatal, neonatal and child outcomes related to poverty-related infectious diseases. Contribute to geospatial epidemiology analyses using GIS-linked eRegistry data. Develop reproducible R-based analysis
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 2 months ago
evaluation. Demonstrated proficiency in programming (Python required). Ability to work independently while contributing to collaborative, interdisciplinary research efforts. Knowledge, Skills & Abilities
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/model documentation, or FAIR data practices. Programming experience in Python, R, Julia, Java, MATSim, GIS tools, or related software. Experience working across disciplines or with stakeholders in
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, tracking, spatio-temporal modeling, edge learning) using field data (traffic cameras, micromobility telemetry, connected vehicle/V2X, crash records, GIS). · Manage and coordinate pilot deployments
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statistics. Knowledge/Skills/Abilities A high level of skill in GIS, computer modeling, data analysis using SAS. Good working knowledge of programming languages VB, R, or Python. Knowledge about coastal