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computational fluid dynamics (CFD), cardiovascular modeling, or biomechanical growth and remodeling. Demonstrated experience with numerical methods (e.g., finite element method), programming languages (C
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excellent accomplishments in research in a broad spectrum of applied and computational mathematics. This includes PDE, calculus of variations, probability and stochastic analysis, numerical analysis, and
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and stochastic analysis, numerical analysis, and scientific machine learning. Interest in interdisciplinary efforts is also valued. Commitment to and experience in teaching and mentoring student
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different numerical tools via Python scripting Experience conducting machine learning and inverse design models HPC experience Experience training and supervising students High proficiency in writing skills