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micromechanical behavior under loading conditions (e.g., tension, compression, creep). Perform detailed microstructural characterization using SEM, EBSD, TEM, XRD, and related techniques. Analyze lattice strain
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/Responsibilities: Perform composites manufacturing using a variety of techniques including compression and/or injection molding, and additive manufacturing Operate characterization techniques such as DSC, FTIR, TGA
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(ORNL) is seeking a highly motivated Postdoctoral Researcher with expertise in artificial intelligence and machine learning (AI/ML), remote sensing, Earth and environmental sciences, and the analysis
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. Conduct in situ neutron or X-ray diffraction experiments to study micromechanical behavior under loading conditions (e.g., tension, compression, creep). Design and execute mechanical testing experiments
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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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guided by AI/ML, remote sensing, process-based modeling, field observations and experiments, and advanced analytical techniques. Major Duties/Responsibilities: Independently and collaboratively lead field
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. The candidate will collaborate with multidisciplinary researchers in robotics, surveying, remote sensing, and artificial intelligence. This on-site position resides in the Building Envelope Materials Research
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, condensed-matter physics, neutron scattering, applied mathematics, and scientific computing. This position resides within the Quantum Sensing and Computing Group in the Computational Sciences and Engineering
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-generation, data-driven manufacturing systems that integrate artificial intelligence, real-time sensing, and digital twins to transform how critical components are designed, produced, and qualified