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equations (PDEs). The position is funded by the Dutch Research Council (NWO) via the Vidi research project Optimal adaptive space-time boundary and finite element methods. The project focuses on the design
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Institut National des Sciences Appliquées de Lyon | Villeurbanne, Rhone Alpes | France | 20 days ago
with the physical principles of structural dynamics and (vibro-)acoustics and the related numerical modeling techniques, such as the Finite Element Method (FEM), as well as numerical optimization
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) professional or academic experience in Machine Learning or finite element modelling. 5. Formalization of the applications: Applications are formalized through a request addressed to the Rector of Universidade do
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of the finite element method (modelling assumptions, boundary conditions, mesh/element choices, convergence checks). Experience with at least one FE tool such as Abaqus or similar. Scientific programming skills
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to the development of next-generation AI-enhanced finite element methods for robust structural design. You will be part of a dynamic and internationally oriented research group with strong expertise in solid mechanics
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constrained-mixture (finite element) models for cardiovascular tissues towards simulating cartilage G&R. You will then simulate cartilage microtissues growing inside engineered, confining microenvironments and
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of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Knowledge of constitutive modelling of materials. Knowledge of non-linear finite element methods. Knowledge
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of the position. The successful candidate will have a solid theoretical foundation in one or more of the topics: Computational Mechanics, Finite Element Analysis (FEA), Numerical Optimization
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programming skills (C++ or Python) and experience with numerical modeling (for instance, Finite Element Analysis or Computational Fluid Dynamics); A strong interest in—and willingness to learn and perform
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. Experience working with Finite Element Method (FEM) tools, such as Abaqus, ANSYS, OrcaFlex, or similar software, is highly regarded. Furthermore, an interest or practical experience in additive manufacturing