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Information Eligibility criteria * Skills/knowledge: statistical physics, physical chemistry, machine learning * Expertise: molecular simulations, programming experience (Python, C++, Julia, C, etc.), Python
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at 900 K) * Developing automated workflows for data acquisition and analysis * Programming in Python and Matlab * Analyzing results and discussing them with the other project partners * Writing scientific
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Bayesian statistics, stochastic modeling, and optimization under uncertainty • Proficiency in Python programming • Strong interest in applied and transferable research • Knowledge of industrial simulation
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molecular spectroscopy and nonlinear optics, and is a must for recruitement. Additional qualifications such as training and supervision of master students, and proficiency in Python and/or Matlab are valuable
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, hydro-acoustics, data science, geodynamics, geophysics, statistics, Bayesian inference ⁃ Experience with statistical analyses and machine learning techniques ⁃ Programming in C / python / Julia
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: electronic structure calculations (plane wave DFT if possible), statistical thermodynamics, molecular dynamics. Skills in Python, bash scripting, Fortran 90 and machine-learning would be appreciated. The PIIM
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Eligibility criteria Strong skills in analyzing single-cell transcriptomic data using Python. Strong skills in analyzing epithelial tissue dynamics. Website for additional job details https://emploi.cnrs.fr
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proficiency with at least one programming language (Perl or Python preferred). Skills in molecular phylogeny are a plus. Other required skills: English (written and oral). Good presentation and communication
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with basic continuum and rock mechanics, including computational approaches. * Programming in C / python / Julia or equivalent, and ideally some experience with high-performance computing * Familiarity
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processing and modelling • Rock mechanics, and inversion • Computation: Linux, Matlab or Python Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR6524-AUDCHA-035/Default.aspx Work