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descent, random forests, etc.) and deep neural network architectures (ResNet and Transformers). Preferred Qualifications: Knowledge of Approximate, Local, Rényi, Bayesian differential privacy, and other
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and physical processes for recovering and purifying radioisotopes from irradiated targets and waste streams. These efforts directly support the DOE IP mission to produce and distribute limited-supply
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, and optimize preprocessing pipelines using HPC resources, targeting scalable execution and automation. Collaborate with domain scientists to integrate pipelines into end-to-end AI workflows specific
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the processing-microstructure-property relationships in aluminum alloy systems. Perform the necessary chemistry and processing modifications to meet target alloy properties. Apply advanced characterization and
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Postdoctoral Research Associate - Theory-in-the-loop of Autonomous Experiments for Materials-by-Desi
integrated autonomous experimental synthesis and characterization cross-facility agentic-AI platforms that allow real-time guidance and control of these multi-modal experiments for targeted discovery of novel
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production target materials. This involves the development of experimental plans to examine material properties such as thermal diffusivity, thermal conductivity, and thermal expansion – material properties
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for the security of our nation today and target our vision on how these challenges may manifest themselves in a decade or more. NSSD’s research and development focuses on cybersecurity and cyber physical resiliency