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computational physics, computational materials, and machine learning and artificial intelligence, using the DOE’s leadership class computing facilities. This position will utilize methods such as finite elements
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material property database for composites. The candidate will utilize the database to develop AI models for composite discovery. The candidate will work with a multidisciplinary team to set up finite element
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. Proficiency in CAD/CAM and finite-element modeling is required, alongside disciplined verification/validation practices and the ability to translate prototypes into reliable, user-ready systems. Demonstrated
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evaluation of alloys; familiarity with finite element methods. Skills and experience in programming, machine learning, or signal processing are all considered a plus. Outstanding UA benefits include health
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-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and uncertainty quantification. The position comes with a travel allowance and access
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to Computational Fluid Dynamics. Mathematical topics of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 2 hours ago
Eulerian (such as finite element) methods can be used. Proposals should acknowledge the benefits and limits of their technique compared to others. Part of the proposal should consider the need
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systems. Knowledge of simulation tools (e.g., Multiphysics finite element analysis, Matlab, Labview etc.) cleanroom experience, and characterization of electronic devices are required. Further, knowledge
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by working to develop novel algorithms on finite element method, isogeometric analysis, geometric modeling, machine learning and digital twins to study various applications such as computational
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of simulation tools (e.g., Multiphysics finite element analysis, Matlab, Labview etc.) cleanroom experience, and characterization of electronic devices are required. Further, knowledge of system level integration