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Field
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safety margins are often required in structural design, leading to heavier structures, while maintenance intervals may be more conservative than necessary. Developing reliable methods to continuously
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. The Risk and Infrastructure Systems Lab, led by Asst. Prof. Alex Sixie Cao, develops quantitative methods for understanding and managing the reliability, robustness, and safety of structures and
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versioned analysis-ready datasets without compromising source-data integrity; maintaining reproducible construct reports with descriptive statistics, scale reliability, tables, figures, and transparent
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maintenance intervals may be more conservative than necessary. Developing reliable methods to continuously assess the structural condition therefore enable both lighter designs and more efficient maintenance
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flow battery stacks from prototype to commercial scale while ensuring performance and reliability. Develop, assemble, and validate stack designs through structured testing, durability studies, and
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development from prototype to commercial scale while ensuring performance and reliability. Develop, assemble, and validate stack designs through structured testing, durability studies, and failure analysis
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intervals may be more conservative than necessary. Developing reliable methods to continuously assess the structural condition therefore enable both lighter designs and more efficient maintenance strategies
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educational assessment, test design, and measurement validity (e.g., content/construct validity, reliability analysis). Experience in data cleaning, dataset management, and handling quantitative survey or test
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web research, web scraping, data collection, dataset construction, data cleaning, and statistical analysis. Generative AI tools may not be used for data collection. This position provides hands
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occasionally into English. Review audio and video data files that will facilitate coding, analysis, and inter-rater reliability; Assist with tasks related to coding, analysis, and inter-rater reliability