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advanced modelling approaches—such as finite element analysis —to capture the nonlinear, multi-physics nature of soft materials. By integrating experimental data and validating simulations, your work will
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Mechanical Engineering Technology Program with Engineering Design (Fusion 360), CAD/CAE (Solid Works), Engineering Computing (Matlab), Finite Element Analysis (Solid Works) skills preferred. A strong
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level (neural network models) including plasticity. Electric fields will be estimated based on finite-element method models. The project can be partly adapted to your specific interests and your
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mitigation. Advanced simulation frameworks will be developed, combining wave & finite element based methods, multi-scale homogenization, and nonlinear modelling to efficiently investigate and evaluate a wide
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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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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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-aided design (CAD) experience and demonstrated proficiency. Finite-element analysis (FEA) experience and demonstrated proficiency. Required Documents Cover letter summarizing your relevant experience and
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. Analyze the proposed and optimized solutions. Write reports. Where to apply Website https://seuelectronica.upc.edu/en/procedures/call-for-recruitment-of-ptgas-staf… Requirements Research FieldEngineering
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leading group in high-order methods: a class of finite element methods that is now leading the way for future computational fluid dynamics simulations. Specifically, our group develops the Nektar++ spectral
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structural characterization; magnetic and structural analysis; preliminary experience with finite-element simulations; and experience in developing hardware and software for control and data acquisition as a