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science, or a related field. Strong background in quantitative methods and statistical analysis. Experience with computational tools for large-scale data analysis (e.g., Python, R, SQL). Familiarity with
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computing tools (Fortran, C/C++, Python, Linux) - fluency in English and proven international experience Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5508-FRARAD-002/Candidater.aspx
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of stochastic systems, and possibly reinforcement learning / POMDPs; ● Has, or will soon acquire, skills in Python or R (or equivalent); ● Is willing and able to move between ENS in the Paris region and SETE in
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Compétences approfondies de programmation en R ou Python Une première expérience d'analyse de données génomiques ou en biostatistique est recommandée. Forte appétence pour le travail multidisciplinaire et en
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beamline operations. • The ability/ willingness to code (Python) is mandatory, data mining is critical to the success of this project. • Proficiency in English (A proof of upper-intermediate B2 level must be
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knowledge of an interpreted language (Python, R, etc.), the knowledge of Netcdf format would be a plus, writing scientific articles (at least one publication as 1st author in a peer-reviewed journal
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accelerator physics • Python (or C++, Fortran) coding • analytical skills • basis of data analysis • a high level of communication skills, both oral and written (French and English required) to be able
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(especially fMRI), experimental design, data analysis and programming (e.g., SPM, MATLAB, Python, R,…), scientific writing, and very good organization and communication skills. The ideal candidate is able
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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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: 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