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catheters – i.e., equipped with multiple electrodes – are increasingly used as they facilitate the electroanatomic mapping of the atria before the ablation phase. However, most ablation strategies neglect
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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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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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for four years. The project involves multiple partners: • OTFT characterizations : L2n-URCA Reims (O. Simonetti) • Polymer synthesis: ICPEES Strasbourg (N. Leclerc) • Material deposition: ICS Strasbourg (M
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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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aims to provide an integrated assessment of urban vegetation from multiple perspectives, including its social functions and usage requirements, the ecosystem health of green spaces linked to plant
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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
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | about 1 month ago
arithmetic cores for FPGAs). The team hosts 6 faculty, 6 PhD students, 3 postdocs, 2 engineer, and multiple research interns. Additional information can be found on team website: https://team.inria.fr/emeraude
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laminar burning velocities by extrapolation) will be quantified by sampling multiple DNS. This work aims to enable the robust inference of kinetic parameters directly from simulations