76 cyber-security-data-analysis Postdoctoral positions at Oak Ridge National Laboratory
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biogeochemistry. Experience applying machine-learning or AI methods to environmental data analysis, model calibration, or model-data integration. Experience synthesizing multi-source, multi-scale observational
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community needs and goals. Deliver ORNL’s mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service. Promote equal opportunity by
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biogeochemistry. Experience applying machine-learning or AI methods to environmental data analysis, model calibration, or model-data integration. Experience synthesizing multi-source, multi-scale observational
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Materials Analysis in the Nuclear Nonproliferation Division in the National Security Sciences Directorate at Oak Ridge National Laboratory (ORNL). Major Duties/Responsibilities: Develop, validate, and extend
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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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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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, 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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-time data acquisition and telemetry systems Familiarity with cloud computing platforms and edge deployment of ML models Experience with uncertainty quantification, sensitivity analysis, or robust
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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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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