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Field
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algorithms) that enable rapid creation of new high-fidelity multi-scale/multi-physics computer models of materials capable of utilizing modern extreme-scale computing environments. The success of multi-scale
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Mexico, and elsewhere), and in relating particle composition to measurements of size distributions, air mass trajectories, etc.; (2) development of algorithms to process complex spectral data and identify
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the development of image/signal processing algorithms from a multidisciplinary approach, to include multiple sensor modalities. These multidisciplinary research opportunities incorporate theoretical and
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and often different from the canonical types of data used to benchmark machine learning (ML) algorithms. In this opportunity, we will be evaluating how state-of-the-art ML techniques can be used