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Field
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distribution. Both projects will develop the Fontan emulator to be patient-specific, MRI compatible, computer controlled, and quantitatively evaluated using advanced bench-top, CFD/FSI simulation, and MRI-based
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. This does not meet the needs of research discovery processes however, as internal researchers likely know the others in their specific discipline and what they’re working on already. Researchers
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various concepts in welding and related mechanical engineering processes and cleaning existing datasets. Creating deep learning models. Using deep learning to create a robust model that predicts welding
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two-year Small Business Technology Transfer project (STTR) funded by the National Science Foundation. The successful candidate is expected to support the development, simulation and testing of model
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 2 months ago
be given the opportunity to copy over what they had previously submitted. All documents must be in English or include an official English translation. If you have questions before, during, or after you
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given to applicants who are in the process of completing their PhD degree. Documentation of PhD degree completion must be provided prior to commencement of employment. Certifications/Licenses Required
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Posting Details Do you have questions about the application process? If so, please refer to the Applicant FAQ’s. Posting Details (Default Section) Posting Number: 20260054F Position Title
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institutional momentum. As UNT Health continues to invest in biomedical discovery, translational science, simulation, and interdisciplinary collaboration, the next Chair will play a central role in advancing
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field in hand by May 2026. Preferred Qualifications: Experience in Thermal Spray Materials/Processes/Characterization/Modeling. Experience in Solid Mechanics/Thermomechanics/Finite Element Analysis
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. Demonstrated expertise in using machine learning and optimization frameworks in conjunction with FE simulations to assist with component and/or process design is preferred. Excellent written and oral