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Landscape analysis and modeling, with a focus on training and application of predictive machine learning tools. This researcher will synthesize regional-scale remote sensing imagery and ecological monitoring
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, SEM, or Raman. Perform data analysis of mass spectrometry (i.e., GC-MS, LC-MS, SIMS) and microscopy data sets and coordinate between experimental studies and theoretical simulations. Communicate
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evolution, phase stress, and defect evolution using advanced data analysis tools. Perform alloy fabrication and processing (e.g., arc melting, heat treatment) and relate processing to performance. Apply
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of projects related to electrochemical analysis, surface specific spectroscopy, and battery materials for vehicle and aircrafts. Applicants are expected to perform experiments to direct and control
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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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for geothermal casing related harsh environments applications. A background in polymer chemistry research or related fields, composite material development, material science, and data analysis is preferred. Strong
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technologies Proficiency in using Excel, Python, R or similar tools for engineering data analysis is preferrable Excellent written and oral communication skills Motivated self-starter with the ability to work
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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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represents expertise in nuclear materials synthesis and analysis, deployment of advanced analytical methods including crystallography, imaging, spectroscopy, physical property analysis, neutron scattering, and
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optimization, and application-driven performance analysis for HPC, scientific Artificial Intelligence (AI), and scientific edge computing. We are a leader in computational and computer science, with signature