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modeling. These projects will focus on how to leverage ideas from a combination of partial differential equation based computational methodologies and machine learning techniques to develop computational
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, brain science, and neuroscience); data science and machine learning; modeling, analysis, simulation and prediction for biological, engineering, physical and quantum systems; probability theory and
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researchers in pursuit of advancing knowledge and making significant contributions to their respective fields. ESSENTIAL QUALIFICATIONS/EXPERIENCES PhD Graduation; Strong background in deep learning, machine
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mathematics. These positions offer excellent interdisciplinary training possibilities in scientific computing, stochastic modeling, perturbation theory, statistics, and machine learning (applied to image and
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, separation, and catalysis, with a focus on carbon capture and conversion technologies. Artificial Intelligence: Leveraging AI and machine learning to optimize material design and catalysis processes. Carbon