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and edge computing; The design of architectures/models which accurately capture the complexities of the data, with robust estimates of confidence in predictions and compressed quantities of interest
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include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a travel allowance and access to advanced
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length scales Develop machine learning algorithms to support process optimization, predictive modeling, and intelligent manufacturing control Integrate simulation tools with in-situ sensor data from
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to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a
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focus on designing architectures and models that effectively capture the complexities of data, provide robust confidence estimates in predictions, and generate compressed quantities of interest tailored
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water distribution, sanitary sewage collection and treatment, compressed air production and distribution, steam production and distribution, storm water system, natural gas distribution, and chilled water
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in predictions and compressed quantities of interest on defined domains; Fast and scalable algorithms to fit the proposed models to data, with a theory that explains the convergence and success
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in scientific research. Knowledge of design and analysis of complex systems using AI. Knowledge of data management, high performance I/O, and data compression methods. Experience working in a cross
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using AI. Knowledge of data management, high performance I/O, and data compression methods. Experience working in a cross-discipline team with other modelers and experimentalists. An excellent record