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(ORNL). As a part of our team, you are responsible for operating critical computing infrastructure for data acquisition, data reduction, data analysis, data management and instrument control systems. You
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technologies supporting operational situational awareness products. These candidates will bring fresh ideas from areas including information retrieval, distributed computing, large-scale system design
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computing or big data architectures. Spatial enabled database (PostgreSQL with PostGIS) and performing spatial data queries. Software development best practices including, but not limited to: Agile
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. The project will focus on research and development of advanced machine learning and deep learning algorithms to analyze large quantities of multimodal images and data arising from the Advanced Plant Phenotyping
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-class research and development in hydrologic and atmospheric system modeling and evaluation, large scale data analytics and ML, and model-data integration at the US Department of Energy’s (DOE’s
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field involving geospatial computing or big data architectures. Experience with one or more of following languages: Python, C/C++, R, C#, Java; knowledgeable in Linux, shell scripting. Experience with
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the Geospatial Science and Human Security Division (GSHSD) at ORNL. The group performs artificial intelligence, computer vision, and federated learning research initiatives, with emphasis on large scale geospatial
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this position, you will research workflow solutions for integrating advanced data science techniques (simulation, machine learning/artificial intelligence, statistical data analysis) across the edge-to-cloud
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. This position supports technical exchanges with foreign counterparts as necessary, and is responsible for integrating the collected raw information with an existing classified electronic document management
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Power BI development and a proven foundation in Data Science, including fundamental-level skills in Generative AI and Machine Learning! This role focuses on designing, developing, and moving BI, Analytics