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Inria, the French national research institute for the digital sciences | Toulouse, Midi Pyrenees | France | 22 days ago
parallel and heterogeneous architectures, permits the integration of advanced interoperable CFD components, including in particular Finite Volume (FV) as well as Finite Element (FE) methods, namely
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%); Experience in analysis and simulation and finite element software for the analysis of building components; energy and thermal simulation (30%); Motivation letter (20%); Proficiency in Portuguese (5%) with
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. Develop multi-physics material models, implement them in a finite element code, and conduct experimental characterisation. The balance between modelling and experiments can be tailored to your interests
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or physics. It is a condition of employment that the doctoral degree has been awarded. Experience from the finite-element method is a requirement. Experience from computational structural dynamics is a
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simulation software developed "in house" known as Fluctuating Finite Element Analysis (FFEA), and you will learn how to improve this software so that we can watch a molecule walk. Funding Notes The position
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• Excellent command of English, both written and spoken. Desirable qualifications • Experience with battery development, electrochemical testing, and reliability assessment • Familiarity with finite element
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collaboration with academics from the Bristol Composites Institute and Rolls-Royce PLC. This will entail introducing and validating finite-element based multiscale and multi-physics modelling methodologies and
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The predictive simulation will be developed through Finite Element Analysis (FEA) in between LMGC and ICube and LEM3 Labs. Therefore, FEA poro-mechanical simulation experience is a plus (Le Floc’h, et al., 2024
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colleagues to understand the stress distribution at the bone-implant interface through finite element analysis. Work collaboratively with other colleagues to validate finite element models based on in situ
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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