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augmented intelligent solutions that monitor, diagnose, and predict process performances to optimize production quality and yield. Proposals are welcome to develop augmented intelligent solutions
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chemical species and ligands that may bind a given adsorbate more or less favorably. These variations allow enormous potential for optimizing physical properties, such as the selective adsorption of one
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, characterize, and optimize interconnects between disparate chip technologies. Applicants will have the opportunity to learn high-demand skills for millimeter-wave technologies including calibration, integrated
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-acquisition circuitry, and signal-processing/pattern-recognition algorithms. The sensors must be tailored for the particular nature of a given chemical or biochemical measurement problem by optimizing and
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-based and data-driven prediction models are often impractical for operational use due to unrealistic assumptions, limited data availability, and prohibitive computational costs. To address
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. Chemical engineers constantly need reliable property data for process design development and optimization. This information is predominantly coming from scientific publications. Thousands of papers
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are designed, constructed and operated to provide optimal spaces for living and working. The industry needs tools, metrics, and processes to create buildings that are more than just static structures but living
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metabolites in situ. The first goal of the project will be to characterize the volatile organic chemical fingerprints of various bacteria using PTR-MS. We will then optimize a rapid, noninvasive workflow for
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learning with machine-controlled measurement tools for closed loop experiment design, execution, and analysis, where experiment design is guided by active learning, Bayesian optimization, and similar methods
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. The postdoc will develop machine learning algorithms to analyze phenotype and sequence data, as well as active learning algorithms to optimize and control experiments in directed evolution. This position