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(e.g. Python, MATLAB or equivalents); Interest in applied thermodynamics, numerical simulation and sustainable energy systems. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR7274-SILLAS
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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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research, possess advanced skills in data handling and scientific programming (Python or equivalent). LanguagesENGLISHLevelExcellent Additional Information Benefits The PhD will be carried out jointly (co
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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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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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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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: 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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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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skills : We expect a candidate with a strong background in machine learning or statistics. The candidate must also be proficient in high-level languages like Python. Familiarity with single-cell date and
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 3 months ago
Python and good analytical skills. A good background in probability/statistics and deep learning is expected. Knowledge of differential privacy and/or fairness is a plus, but not necessary. The candidate