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interests are interdisciplinary modeling (ideally using economic production theory, more specifically Data Envelopment Analysis, system dynamics modeling/agent-based modeling, and/or Artificial Intelligence
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distribution systems. Current research initiatives include developing advanced vibration analysis methodologies for wooden packaging systems, predictive modeling for packaging performance, and optimization
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predictive modeling approaches to understand corrosion mechanisms and coolant/fuel chemistry in extreme conditions. The successful candidate will oversee corrosion-focused projects sponsored by industry and/or
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statistical and mathematical modeling. PhD must be awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility remaining. • Research in mathematical
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, sustainable materials, or engineering to contribute to our ongoing research on improving the hygrothermal performance, structural modeling, and durability of CLT, including hybrid and thermally modified wood
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-based models, and remote sensing technologies. Required Qualifications • Ph.D. in Civil or Environmental Engineering, Hydrology, Data Science, Geosciences, Computer Science, or a related field. PhD must
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supervision of Prof. Yingda Cheng on computational methods and modeling for kinetic equations. The research conducted will involve development of numerical methods, development and analysis of reduced order
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candidate will play a key role in developing and advancing new models and simulations for Computational Fluid Dynamics (CFD) hypersonic codes. Specific tasks include developing new turbulence and transition
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jurisdictions utilizing land use-value assessment estimates. Duties include, but are not limited to: development of computational methods, maintenance of current models and data sets, identifying and testing
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modeling. PhD must be awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility remaining. • Experience with analysis of time series data. • Solid