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the Philip Leverhulme Prize. We are looking for a researcher interested in running coupled chemo-mechanical finite element simulations to address mechanical challenges that are holding back
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health. Specifically, our approach combines finite element modelling and medical image analysis. Our finite element brain models are based on tissue segmentation and our numerical simulations are validated
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of experimental data - Molecular Dynamics and Finite Element calculations. . Metallic nanoparticles (NPs) exhibit unique physico-chemical properties departing from those of bulk materials, primarily due
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expertise in the analysis and design of concrete structures. Advanced proficiency in Finite Element Modelling (FEM) using tools such as Abaqus, ANSYS, RFEM, SAP2000, MIDAS or equivalent. Solid understanding
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in a finite element code. Study the different dynamic regimes depending on the model parameters. Where to apply Website https://seuelectronica.upc.edu/en/procedures/call-for-recruitment-of-pdi-postdo
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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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mathematics. An important aspect of the ongoing research is solving stochastic partial differential equations on surfaces, e.g., with surface finite element methods. The following requirements are mandatory: A
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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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structure-preserving discretization algorithms (a refinement of finite-element analysis compatible with exact geometric, topological, and physical constraints) with artificial neural networks for achieving
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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