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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 37 minutes ago
simulation (such as bonded particle) and 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
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. Ability to perform finite element simulations using software such as COMSOL, ANSYS, or ABAQUS. Experience in utilizing these tools for in-depth analysis is highly desirable. Required License/Registration
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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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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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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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heavy software development component. The successful candidate will perform research in the application of machine learning (ML) techniques to the finite element method (FEM) in the context of composites
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finite element analysis and modal analysis techniques. • Experience with vibration analysis, dynamic testing, or mechanical systems characterization. • Proven record of publishing refereed journal articles
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transformations and also of finite element simulations of shape memory alloys. Physical experiments involve differential scanning calorimetry, thermomechanical testing, and potential nanoindentation of shape memory
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), mechanical testing, or non-destructive evaluation of metals and alloys. Hands-on experience skillsets with finite element methods (ABAQUS), programming languages (Python, MATLAB, C++), experience in signal
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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