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Multi-scale modeling of the evolution of structure and properties in materials for nuclear energy applications
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Events
Events
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Gradient-Based Multidisciplinary Design Optimization for Propeller Design | Validation of a multivariate non-Gaussian, non-stationary wind pressure simulation model for performance-based wind engineering |
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Efficient calculations of electronic structures with machine-learning models |
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The U-M Data Science and AI Summit is the largest annual data science and AI event on campus. This event brings together the U-M data science and AI research community and their external collaborators to build research vision and collaboration. It also showcases the breadth and depth of U-M data science and AI research, from […] |
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The U-M Data Science and AI Summit is the largest annual data science and AI event on campus. This event brings together the U-M data science and AI research community and their external collaborators to build research vision and collaboration. It also showcases the breadth and depth of U-M data science and AI research, from […]
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Active Learning for Physics Informed Data Sampling and Construction of Free Energy Representations |
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Women in Computational ScienceThe Women in Computational Science Symposium is the inaugural event for MICDE's DISCOVER (Diversity and Innovation in Scientific Computing: Opportunities for Valuing Exploration and Representation) mini-symposium series. This mini-symposium provides a unique opportunity to delve into the pioneering research conducted by women in computational science while also gaining insight into their personal […] |
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