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will use and develop Python scripts for analysing results and may participate in the development of codes such as the observation simulator and the improvement of the controller. The proposed thesis will
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proficiency in Python. Knowledge in Statistical physics and Network science, and interest in complex networks and interdisciplinary research are a plus. The position is for 3 years, and will be located
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to the field - programming/coding in Python (Pytorch) - presentation of results at conferences - interaction with team members and international collaborators Where to apply Website https://emploi.cnrs.fr
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)chemistry and expertise in MD simulations, quantum chemistry or machine learning. Knowledge of biosystems, analysis skills (Python), scripting skills (bash and/or Python) and machine learning are assets
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datasets; • Strong analytical and statistical skills (preferably in R or Python); ability to analyse spatial data (with GDAL/PDAL via R or Python) ; • Solid background in fire ecology, ecosystem functioning
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- python programming Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR8214-SANLEV-038/Default.aspx Work Location(s) Number of offers available1Company/InstituteInstitut des Sciences
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learning applied to dynamic systems; Proficiency in key machine learning libraries (PyTorch, JAX, etc.); Mastery of Python and the software ecosystem for scientific data analysis and management (NumPy
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related), molecular dynamics (GROMACS, NAMD) and docking (VINA and derivatives). - Proficiency in Python and Fortran languages and Bash scripting. - Proficiency in RDKIT and BioPython. - Proficiency in
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development and data analysis will be required. A solid knowledge of Python and/or C++ is also essential for this position. Finally, a good command of spoken and written English is required. Additional comments
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, library preparation, cell culture, and imaging - Proficiency in computer languages (bash, python, awk, R) - NGS/omics data analysis - Proficiency in statistics for high-throughput data analysis - Generation