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responsible for conducting numerical and theoretical studies of turbulent flows and their associated geometric structures, focusing on passive and active scalar fronts, multiphase mixing layers, and
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project focused on the development machine-learning powered digital twin system for the structural performance of civil engineering structures. The project is a collaboration between multiple research
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project focused on the development machine-learning powered digital twin system for the structural performance of civil engineering structures. The project is a collaboration between multiple research
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wearable setting. Dehydration of workers lead to performance drop, and stroke by dehydration poses serious risks in construction sites. Current wearable methods for detecting dehydration are typically based
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of sensory neuroscience and expertise in at least one of the imaging methodologies involved in the project (OCT-A, structural MRI, fMRI, dMRI, ASL). For a competitive application at the post-doctoral level
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, CFP, BET, FT-IR, Raman spectroscopy, among others. Lab-scale testing will be performed to establish critical relationships between fabrication methods, structure, properties, and membrane performance
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of large strain (antigenic) diversity, network descriptions of strain structure, and implications for resilience to perturbations. We are also more generally interested in extensions of this work to other
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-based analysis applied to underground structures. Advanced subsurface characterization techniques integrating geotechnical and geophysical data. Geohazard mapping and modeling, including tunnel-induced