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in multiscale and multifidelity simulation techniques (ab initio methods at different fidelity, machine learning tight-binding, machine learning force fields, phase-field modeling, and/or kinetic monte
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biology, bioinformatics, mathematics, physics, engineering, computer science, or a related field. Computational background in areas such as AI/deep learning, multiscale modeling, optimization, topological
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injury, and bleeding pelvic fractures using a very large in-house CT dataset with high-quality labeling and outcome data . 2) Training and validation of state-of-the-art segmentation models
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