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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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. Responsibilities: • Design and conduct experimental research on paper-based materials for food packaging applications. • Develop predictive models for packaging performance using machine learning and physicochemical
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systems. • Develop and implement predictive models for packaging performance using machine learning approaches and physics-based simulations. • Investigate logistics optimization strategies for packaging
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stress contagion and collective motion, as well as survey data of emotional states and personality metrics. Modeling efforts will focus on agent-based approaches, which may include both simulation studies
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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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-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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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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models and machine learning techniques for kinetic equations arising from plasma and neutron transport. The position will be based at Virginia Tech’s campus in Blacksburg, VA. The postdoc will have a
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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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; generating CFD datasets using new models for specific applications. This position is based at Virginia Tech's main campus in Blacksburg, VA and offers opportunities for teaching and service-related activities