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Lecturer MECH 546 - Finite Element Methods in Solid Mechanics (3 credits) Teaching Qualification Requirements: Minimum of Ph.D. in Mechanical Engineering. Minimum of three years’ experience teaching or in
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | about 2 months ago
., & Sen, M. K. (2007). Grid dispersion and stability criteria of some common finite‐element methods for acoustic and elastic wave equations. Geophysics. Chaljub, E., et al. (2007). Spectral element analysis
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 2 months ago
coupling with adaptive meshes. High-order spectral finite element methods (SFEM) offer superior accuracy per degree of freedom and are naturally suited to HPC architectures (CPU/GPU clusters). Two main
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-time data acquisition during production, consulting, and prototype manufacturing. Graph neural networks provide an opportunity to operate on Mesh structured data utilized in Finite Element Method (FEM
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conventional simulators. Finite element-based methods such as Mixed-Finite-Element or Control-Volume methods are convenient thanks to their suitability for complex unstructured grids. Applications are sought
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Simulating Composite Fracture by the Extended Finite Element Method School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Dr J L Curiel Sosa Application Deadline
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, finite element analysis, programming and numerical methods. Applicants are expected to have achieved a First class (or, in special cases, an upper-class, 2:1) honours MEng/MSc degree or equivalent in
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. Candidates are expected to have a strong background in at least one of the following areas: numerical analysis and/or simulation methods for PDEs (in particular finite volume or finite element methods
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are in ProEngineer and finite Element Software. PhD degree is required with prior teaching with minimum of two years technical and teaching experience. The University of Miami is an Equal Opportunity
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learning methods, featuring regularizing terms involving differential equations, suitably discretized using finite element schemes. Particular care will be devote to be implementation of the proposed methods