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languages R or Java will be appreciated. Previous experience with phylogenetics will be an advantage but is not required. The candidate must have good communication skills (oral and written) in English, and
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- evolutionary theories ● Interpretation and formatting of the results obtained (publications) ● Proficiency in programming languages (Bash, Python, R), code management tools and software environments (Gitlab
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collaboration with a major cosmetics manufacturer, and provide ample opportunity for research stays at the manufacturer's R&D facilities in Paris. With more than 750 researchers, the FEMTO-ST Institute (CNRS
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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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/nanotechnologies, microelectronics or materials. • English language (B2 to C1). • Experience (projects or internships) linked with R&D and physical measurements will be welcome. Operational skills : • Listening
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. • Demonstrated skills in bioinformatic and statistical analyses of microbiome and ecological data including sequencing data. • Analysis skills: write and execute code in R, Python, GitHub etc., high-performance
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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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(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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have excellent skills in analyzing human behavior and be proficient with experimental and data processing software (E-Prime, Matlab, R), statistical analyses including linear mixed-effects models, as
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. Loubière, T. Neveux, R. Privat, and T. Nabil. “Representation Learning for Flowsheets: Generating Structures for Process Synthesis”. In: ESCAPE34- PSE24 Books of Abstracts. 2024, p. 01. doi: 10.3303/BOA2401