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systems for accelerating computational catalysis and experimental design. The successful candidate will contribute to building AI-native frameworks that combine first-principles modeling, machine-learning
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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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initiatives include developing advanced aqueous emulsion and suspension systems for spray coating, predictive modeling of packaging performance, and optimizing packaging designs for high-value product
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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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aegypti genome, including their distribution across the global tropics and their role in the mosquitoes' adaptation to different climatic variables. The candidate will also study the molecular basis
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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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. The position involves research in modeling and simulation of within-host virus dynamics, theoretical immunology and multiscale immune-epidemiological models of infectious diseases and teaching two classes per
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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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candidate will join Dr. Siddharth Saksena’s research group, which focuses on advancing hydrologic modeling, flood forecasting, and hydroinformatics through the integration of artificial intelligence, physics
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of causal machine learning and optimal policy learning. • Proficiency in other languages such as Stata, and/or Python modeling languages. • Research experience using Python. • Experience working with large