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Instituto de Geografia e Ordenamento do Território da Universidade de Lisboa | Portugal | about 1 month ago
follows: 1. Preparation, processing, and validation of geospatial data; 2. Collection, harmonization, and quality control of cartographic data; 3. Validation of spatial and morphological criteria
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candidate is expected to teach courses in advanced and emerging geospatial technologies, including GEOG 105 – The Digital Earth, GEOG 263 – Introduction to GIS and advanced courses such as Spatial Programming
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analytics, remote sensing, GIS, and/or hydrology to join our team. This multi-institutional research program spans five institutions across the state of New Mexico including collaboration with Sandia National
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visualization, geospatial analysis, and statistical clustering methods to develop a typology of interface conditions. The doctoral student will also lead an empirical study assessing how different interface types
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Texas communities become more resilient over the longer term. To learn more, visit https://idrt.tamug.edu What We Want We seek a highly skilled and collaborative Data Scientist to lead the development and
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expertise in Geographic Information Systems (GIS), remote sensing and geospatial analytics, urban sustainability, green infrastructure, and/or open space. This position is 75% teaching and mentoring and 25
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computational frameworks that combine 4D point cloud data, geospatial analysis, and advanced ML/DL algorithms. Integrate dynamic environmental datasets into immersive and interactive prototypes for scenario
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options Employee and dependent educational benefits Life insurance coverage Employee discounts programs For detailed information on benefits and eligibility, please visit: http://uhr.rutgers.edu/benefits
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such as geospatial programming, spatial database systems, GIS field methods, spatiotemporal statistics, foundational undergraduate and graduate-level GIS courses, and thematic courses such as GIS
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focused on integrated approaches to geospatial systems analysis. Our work applies a complex adaptive systems approach that explicitly emphasizes behavioural models of human action-taking and decision-making