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: Applications accepted all year round Details Data assimilation combines physical models with experimental or numerical data to produce dynamically consistent flow reconstructions. In turbulence, where full
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understanding of numerical methods and scientific data analysis Ability to read and understand existing scientific code, including Matlab Ability to work independently while communicating progress clearly with
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their work on the NIH-funded project. We especially encourage applicants with demonstrated experience in Hispanic/Latino health and mixed-methods research. We also seek candidates who are eager to expand
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measurement techniques). Desirable additional qualifications include knowledge in additive manufacturing (3D printing) and experience with numerical simulation methods (e.g., finite element methods, FE
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information about our compensation scales is available at: https://apptrkr.com/get_redirect.php?id=7054931&targetURL= COMPENSATION: Pay Rate: $27.00-$32.00 per hour This represents the good faith estimate
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modeling to create a predictive tool that spans orders of magnitude in length and time. Hands-On Numerical Modeling: Implement your model in a custom-made data analysis tool that uses advanced optimization
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Job Purpose To make a leading contribution to “Numerical Modelling of Superconducting Cables” working with “Propulsion, Electrification & Superconductivity” group in the research disciplines
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a solid platform for the PhD candidate. Job description The student will be involved in tasks such as: To collect air samples To apply microbiological methods such as qPCR and sequencing to identify
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finite-difference resolvent solver incorporating stabilising filters as well as a domain-decomposition strategy suitable for complex geometries, - Use efficient time-integration methods to compute
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modeling of polymeric, reinforced, and porous materials, with strong expertise in large deformations and numerical homogenization. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7649-JULDIA