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: Position 1: Postdoctoral Associate – Software Engineering & Technical Development Proficiency in Python, geospatial libraries, API design (e.g., FastAPI), and cloud/HPC environments. Experience with
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, Geoscience, Soil Science, Physics, or related fields). Preferred skills: Commitment to contributing to outreach activities and research dissemination. Experience in computer programming (R+, Matlab, Python
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biogeochemical properties. The post-doctoral researcher will also contribute to the development of GIS-based geo-pedological tools for land unit delineation and sustainable land evaluation...Omissis. Where
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programming skills (e.g., Python, Ruby, PowerShell). A good working knowledge of Artificial Intelligence (AI) principles. Including LLMs and the use of AI Agents Experience working with GIS systems and
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the design of evidence-based interventions within a unified GIS-enabled decision-support platform. Key Responsibilities: Integrate and manage multi-source transport datasets, including traffic flow, telematics
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supporting the design of evidence-based interventions within a unified GIS-enabled decision-support platform. Key Responsibilities: Lead and drive the overall project execution, including research direction
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 4 hours ago
. This research may include analysis of regional and global stress fields for fracture formation. Mapping using Geographic Information Systems (GIS) tools can be used to constrain the mechanisms and stresses
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) data sets in R or Python as well as GIS software such as QGIS or ArcGIS Pro. Knowledge of US forest ecosystems and background in analyzing forest structure, stand dynamics, biodiversity, and/or other
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graduate level: 1) Introduction to GIS; 2) Advanced GIS; 3) Remote Sensing; and 4) Python Programming for GIS. Depending on the needs of SES and the candidate’s areas of interest and/or expertise, other
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advanced programming skills (e.g., Python, R, or similar) and are comfortable working with large datasets. You have a solid quantitative background, with coursework in Finance and Econometrics considered