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, and remote-sensing data) to support model benchmarking, parameterization, and uncertainty quantification. Explore and apply AI/ML approaches (e.g., machine-learning emulators, surrogate modeling, AI
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, and remote-sensing data) to support model benchmarking, parameterization, and uncertainty quantification. Explore and apply AI/ML approaches (e.g., machine-learning emulators, surrogate modeling, AI
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Biogeochemistry. This researcher will use field observations and laboratory mesocosms to investigate how plant traits and soil properties confer resilience or vulnerability to disturbance in coastal wetlands
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delivering solutions to pressing energy storage problems essential to economic develop and security of the United States. As part of our research team, the candidate will be expected to work across a variety
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into closed-loop control frameworks Test and validate control algorithms through simulation, hardware-in-the-loop testing, and/or physical testbeds Apply machine learning techniques to predict thermal system
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: Conduct research and develop next-generation CFD methods (with finite volume and finite element techniques) and models for a variety of nuclear energy systems, using world-leading high-performance computing
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-liquid and liquid-liquid separation experiments to meet project goals Use analytical techniques such as NMR, MS, FT-IR, TGA, DSC, XRD, BET, SEM for characterization. Perform ion separation experiments, use
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Requisition Id 17067 Overview: For this role, we are seeking an enthusiastic postdoctoral researcher to either refine or develop their expertise in composites manufacturing and characterization. As
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Requisition Id 17001 Overview: Oak Ridge National Laboratory (ORNL) is the largest US Department of Energy (DOE) science and energy laboratory, conducting basic and applied research to deliver
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(NSSD). In this role, you will conduct fundamental research into the integration of Bayesian methodologies with system dynamics modeling, advancing statistical methods and the open-source scientific