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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 2 hours ago
geospatial data processing and python programming. Candidates should also have knowledge of optical, lidar, and ground penetrating radar sensing systems and understanding of pavement structures and condition
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scientific concepts to diverse audiences. Proficiency in computer programming (R, Python, or similar languages). This job posting reflects the general nature and level of work expected of the selected
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on research carried out within the ECUME GIS (e.g. Simon Police’s PhD thesis). To this end, working groups will be organised with GIS stakeholders and experts in maritime spatial planning, and realistic
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with data analysis/modelling and programming (R or Python). Advantageous: geostatistics, digital soil mapping, remote sensing, GIS, big data or cloud tools. Proactive working style, strong communication
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field preferred. •Experience with GIS-based programming (Python, Arcade), and application development experience in web/desktop environment (e.g., R, JavaScript, Python, CSS, and Tableau); and vector
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disadvantaged under county‑level payment rules. Your role will involve: Extracting and processing geospatial data from CDL, Sentinel‑2 L2A, NASS QuickStats, NLCD, and Kentucky GIS portals Computing vegetation
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training and experience in statistical analysis, coding (e.g., R, Python or similar), and Geographic IT (e.g., GIS, spatial analysis and modeling). Ability to work both independently and collaboratively
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interest in Earth system and climate change sciences; hands-on and curiosity-driven, and ability to work independently and collaboratively; affinity with object-oriented coding (preferably Python), GIS and
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 3 hours 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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programming, working closely with the GIS Research Fellow and interdisciplinary project team members to create a user-friendly, scalable decision-support tool for planners and policymakers. As part of