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NIST only participates in the February and August reviews. The Materials Reliability Division at NIST houses one of the nation’s leading laboratories for testing the reliability of structural
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must hold a PhD in Structural Engineering, Civil Engineering, or a closely related field, with specialization in structural reliability, probabilistic methods, infrastructure assessment, or durability
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electrodes using various electron microscopy techniques (e.g. FIB-SEM); (ii) Reconstruction of the 3D structure through image analysis; (iii) Analysis of images from new and aged membrane-electrode assemblies
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research background in structural reliability and probabilistic/semi-probabilistic analysis, as well as safety formats for structural design and assessment - Documented experience with time-variant models
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, transfection, mammalian gene and protein expression analysis, and virus production and propagation. Expertise in project relevant areas, such as HIV replication, vector construction and modification, aptamer
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equipment health, availability, and resilience under flexible operating conditions. Combine AI-based insights with LEAN and Six Sigma methodologies to support structured root cause analysis and continuous
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) (Dr. Simpson’s webpage). The original call for the solicitation can be found here: https://www.energy.ca.gov/solicitations/2025-02/gfo-24-307-advancing-designs-and-analysis-high-voltage-direct-current
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datasets, spreadsheets, or structured documents. Assist with basic data analysis, such as descriptive statistics, simple comparisons, trend identification, or visualizations under faculty guidance
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communication skills in English (written and spoken); German language skills are advantageous but not required - Prior experience in medical AI or clinical data analysis is a plus What We Offer - A structured PhD
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for engineering, surveys, system or program analysis; support of design and construction of new or renovated buildings; and setting goals and tracking organizational performance. The Assistant Director of