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) to work on the Terrestrial Ecosystem Science Scientific Focus Area (TES SFA). The successful candidate will contribute to the development and evaluation of the Energy Exascale Earth System Model's land
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) to work on the Terrestrial Ecosystem Science Scientific Focus Area (TES SFA). The successful candidate will contribute to the development and evaluation of the Energy Exascale Earth System Model's land
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data and develop data-driven methods for predicting land loss and ecosystem transitions in wetland-rich landscapes of the Gulf Coast with a focus on coastal Louisiana. This candidate will directly
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of large-scale geospatial and time-series datasets. The candidate will develop and evaluate multimodal AI models to characterize vegetation and land-surface dynamics and quantify ecosystem responses and
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in the areas of Hydrological and Earth System Modeling and Artificial Intelligence (AI). The successful candidate will have a strong background in computational science, data analysis, and process
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general business skills. Preferred Qualifications: Demonstrated ability to multi-task, display initiative, and solve problems. Experience with SAP Ariba procurement system. Solid understanding of the ORNL
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Requisition Id 17095 Overview: Oak Ridge National Laboratory (ORNL) is the largest US Department of Energy science and energy laboratory, conducting basic and applied research to deliver ground
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general business skills. Preferred Qualifications: Demonstrated ability to multi-task, display initiative, and solve problems. Experience with SAP Ariba procurement system. Solid understanding of the ORNL
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Requisition Id 17131 Overview: Oak Ridge National Laboratory is the largest US Department of Energy science and energy laboratory, conducting basic and applied research to deliver transformative
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efficiency and support reliable, repeatable processes Preferred Qualifications: Experience building or maturing a new SharePoint collaboration environment from the ground up Experience working directly with