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Requisition Id 16889 Overview: The National Center for Computational Sciences (NCCS) provides state-of-the-art computational and data science infrastructure for technical and scientific
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techniques capable of maintaining relationships between data and metadata. Collaborate on innovative solutions to automate and optimize the interplay between large scientific simulations, data ingestion, and
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harsh environment applications. Develop data acquisition and control systems that include hydraulic or pneumatic actuation and pressure monitoring combined with interrogation of optical fiber-based
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to enable scientific discovery across the physical sciences, engineered systems, and biomedicine and health. It provides foundations and advances in quantum information sciences to enable quantum computers
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Language Models (LLMs). Distributed Machine Learning: Specialization in data parallelism, model-parallelism, and collective communication strategies in large-scale environments. Proficiency in frameworks
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methodologies as well as subsized mechanical testing methodologies on highly irradiated materials (either using ions or research reactor irradiation data) for establishing performance envelopes for materials
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) Fixed-effects panel models Matching methods (PSM, CEM, nearest-neighbor) Regression-based normalization Longitudinal and cross-sectional data analysis. Experience working with large administrative
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large datasets, including sequencing and ‘omics data Proven publication record Excellent written and oral communication skills Motivated self-starter with the ability to work independently and to
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electronics wastes. In this effort, the candidate will have a direct impact in informing the U.S. Department of Energy’s approach to e-waste recycling. The second approach involves supporting manufacturers and
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. Excellent analytical skills with high attention to detail. Experience with geospatial data visualization tools such as ArcGIS, Cesium, or similar. Familiarity with urban-scale building energy modeling