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for supporting the data management, analysis, and visualization efforts within the Center’s Data Informatics Group (DIG) and for the NJ Climate Change Resource Center, which is also under the directorship
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recognized leader in cartographic design, dynamic mapping, mobile application development, spatial data analysis, visualization, and GIS. The Lab conducts interdisciplinary collaborative projects with research
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software for management and analysis of qualitative data · Effectively develop appropriate qualitative data collection tools, including but not limited to semi-structured and unstructured interview
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to 10 pounds of force constantly to move objects. Visual Acuity: Employee is required to have close visual acuity to perform an activity such as: preparing and analyzing data and figures; transcribing
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. • Expertise in one or more of the following areas: statistical analysis of large data sets, machine learning, data visualization, and a high level of independence with a publication record to support these
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George Washington University | Washington, District of Columbia | United States | about 11 hours ago
, or coursework in sciences, computer sciences, or other engineering related fields. Experience with data analysis, GIS, coding, visualization, or computational research tools. Familiarity with research data
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particular emphasis on integrating satellite LiDAR and UAV data with field observations. Applying statistical modelling, automated machine learning approaches, and artificial intelligence for the analysis and
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for supporting the data management, analysis, and visualization efforts within the Center’s Data Informatics Group (DIG) and for the NJ Climate Change Resource Center, which is also under the directorship
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techniques through virtual reality to transform the way model grids are explored. Immersion will enable interactive (and collaborative) visual analysis, facilitate model comparison, and improve the estimation
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procedures to ensure consistent and reliable data collection across multiple samples. Implement diagnostic methods, such as fiber index profiling and microscopic visual inspection, to analyze post-processing