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models to analyze and mitigate fine particulate matter (PM2.5) exposure from various infrastructure systems (e.g., transportation networks, manufacturing systems, and truck routing). Assessing
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generative AI models to establish structure-property relationships for materials discovery. This individual will be expected to collaborate closely with the project team and coordinate efforts with
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models to analyze and mitigate fine particulate matter (PM2.5) exposure from various infrastructure systems (e.g., transportation networks, manufacturing systems, and truck routing). Assessing
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; expertise in computational mechanics and finite element simulation and modeling; expertise in laboratory and multi-scale experimental testing at the material, component, and structural levels. The candidates
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strong collaboration with the SHORES multidisciplinary research teams. The project will be focused on advanced modeling of coupled fracture/damage of geomechanical materials when subjected a range of
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networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis
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Fabrication of Polymer Medical Devices. The successful applicant will collaborate with faculty and researchers at CENTMED to enhance the surface chemistry of implant materials, improving biocompatibility and