74 gis-python-"NTNU---Norwegian-University-of-Science-and-Technology" positions at University of Texas at Austin
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. Proficiency in tools such as GIS, Python/SQL, data visualization, or lifecycle/techno-economic analysis. Knowledge of the energy-water nexus, regulatory permitting pathways, and/or digital infrastructure growth
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) data analytics, wrangling, management, and synthesis, (b) numerical and analytical modeling environments (e.g. Python), (c) geoprocessing and GIS analytics, and (d) data-driven model development
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synthesis, (b) numerical and analytical modeling environments (e.g. Python), (c) geoprocessing and GIS analytics, and (d) data-driven model development. Demonstrated ability to meet deadlines and effectively
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) years of professional experience in a hydrology context with: (a) data analytics, wrangling, management, and synthesis, (b) numerical and analytical modeling environments (e.g. Python), (c) geoprocessing
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: (a) data analytics, wrangling, management, and synthesis, (b) numerical and analytical modeling environments (e.g. Python), (c) geoprocessing and GIS analytics, and (d) data-driven model development
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synthesis, (b) numerical and analytical modeling environments (e.g. Python), (c) geoprocessing and GIS analytics, and (d) data-driven model development. Demonstrated ability to meet deadlines and effectively
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, thin sections, and well-logs). Experience with database design, data modeling, and data management systems. Proficiency in programming or scripting languages (e.g., Python, SQL) for data handling and
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within the past 3 years in Environmental Science, Geography, Computer Science, Atmospheric Sciences, or related field. Advanced GIS and geospatial computing expertise. Demonstrated commitment and ability
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goals and findings Required Qualifications Bachelor's degree in Computer Science, Industrial Engineering, Mathematics, Statistics, or a related field. Experience with Python. Preferred Qualifications
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sciences, engineering, related technical area Demonstrated ability in Python or similar abstract language. Demonstrated knowledge in one or more of the following areas: machine learning, high-performance