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Field
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-oriented research setting. Strong skills in written communication, report writing, quantitative, qualitative, and geospatial analysis, and policy research and analysis. Comfort and flexibility with working
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information systems to assist researchers, faculty, and students in visually telling their stories with maps and other geospatial tools. We build custom research applications and websites, using stable and
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. Candidates with interests and experience in applied research emphasizing novel plant protection strategies drawn from applying modern geospatial techniques from field- to landscape scales to improve
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. Familiarity with data formats common in scientific domains such as medical imaging, genomic sequences, proteins, chemical structures, geospatial, oceanographic, and heath record data. Experience in CUDA GPU
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applications across all areas of Civil and Environmental Engineering, including (but not limited to) structural engineering, geotechnics, geospatial technologies, innovative construction materials, digital
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database analyses, biostatistics, geospatial analysis, and artificial intelligence, the DSI seeks to foster innovation and collaboration. If you would like to discuss the role further prior to applying
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investigating resilience across spatial scales using geospatial modeling approaches, and/or ability to work with large datasets. Candidates that can contribute to the establishment of new research initiatives
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or humanresources@tmcc.edu . Job Description We want you! Truckee Meadows Community College (TMCC) is recruiting Part-Time Faculty to teach courses in physical geography, human geography, and geospatial tools
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Research Group (GERG), the Center for Autonomous Vehicles and Sensor Systems (CANVASS), the Offshore Technology Research Center (OTRC), the Center for Geospatial Sciences’ Application and Technology Group
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demonstrating well-documented, and modular code (e.g., via GitHub). Exposure to geospatial analysis or spatial data visualization. Knowledge of web scraping or use of APIs to retrieve external data. Experience