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are looking for a specialist in radiation–matter interactions with proven experience in Monte Carlo simulations and programming in C++ and Python. The candidate will work within a dynamic international
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applications from candidates that hold a PhD in Physics or a related area. The successful candidate is expected to have an excellent background in soft matter physics, experience in programming (e.g., python, C
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candidate has experience in coding numerical solutions to partial differential equations via the finite element method / finite differences schemes and programming skills in Mathematica, Matlab, Python
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., Python, R, MATLAB, or similar) are desirable. Ability to work independently as well as collaboratively in an interdisciplinary and international research team. Good command of written and spoken English
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Experience in AI Familiarity with development tools and software environments: Julia, Python Abilities and skills: Ability to work in teams on national or international research projects with academic and
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) - Very good acoustic analysis skills - Good knowledge of speech production models - Very good statistical analysis skills - Good academic English skills (C1) - Very good programming skills (Matlab, Python
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Bayesian statistics, stochastic modeling, and optimization under uncertainty • Proficiency in Python programming • Strong interest in applied and transferable research • Knowledge of industrial simulation
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required (e.g., Python, Mathematica, Matlab). Some knowledge of nonequilibrium statistical mechanics (Boltzmann and Vlasov equations) and magnetism (spin dynamics, Landau-Lifshitz-Gilbert equation) is
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Eligibility criteria Strong skills in analyzing single-cell transcriptomic data using Python. Strong skills in analyzing epithelial tissue dynamics. Website for additional job details https://emploi.cnrs.fr
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molecular spectroscopy and nonlinear optics, and is a must for recruitement. Additional qualifications such as training and supervision of master students, and proficiency in Python and/or Matlab are valuable