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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
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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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(target journals: International Journal for Numerical Methods in Engineering – IJNME). Deep learning algorithms for high-temperature multiphase problems (target journals: Computer Methods in Applied
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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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, Process Engineering, Computational Science, or a related discipline Strong foundation in fluid mechanics, gas–liquid two-phase flows, numerical methods (FVM, FEM), and two-phase flow instrumentation
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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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-Documented ability to teach a range of core and advanced courses in mathematics (e.g., calculus sequence, linear algebra, differential equations, probability and statistics, numerical methods, optimization
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, prepares research and analysis leading to cost effective event operations, develops plans and projections, evaluates and reconciles budget reports, and determines operational methods, processes, and
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position is the development of novel machine learning methods for modeling molecular properties, in particular regression models for bi-molecular properties. The research is embedded in the thematic context
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community ranked as one of the best places to live in the U.S. The growing region surrounding Fayetteville is home to numerous Fortune 500 companies and one of the nation’s strongest economies. Northwest