As a post-doctoral researcher with over seven years of experience, including a PhD, I conduct impactful research across diverse physics domains. My expertise spans quantum computing, entanglement, atmospheric turbulence, hydrodynamics, and cold atoms.An essential aspect of my job is to extract valuable insights and patterns from data, e.g., using machine learning (see "relevant articles" section).Proficient in Python, PyTorch, Mathematica, and C++.I have also a proven track record of successfully supervising students at various academic levels, from bachelor to PhD, and I'm currently teaching at the university and at ENS Paris at the master's level. - Relevant skills: conduct research, expertise in various area of physics, data analysis, coding, communication and presentation skills, project management.- Relevant articles:Correlation-pattern-based Continuous-variable Entanglement Detection through Neural Networks, Xiaoting Gao, Mathieu Isoard, et al., arXiv:2310.20570 (2023), https://arxiv.org/pdf/2310.20570.pdfMetrological detection of purely-non-Gaussian entanglement, David Barral, Mathieu Isoard, et al., arXiv:2301.03909 (2023), https://arxiv.org/pdf/2301.03909.pdfHighly Transmitting Modes of Light in Dynamic Atmospheric Turbulence, David Bachmann, Mathieu Isoard, et al., Physical Review Letters 130 (7), 073801 (2023), https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.130.073801PhD thesis: Theoretical study of quantum correlations and nonlinear fluctuations in quantum gases, Mathieu Isoard (2020), https://theses.hal.science/tel-02974737/file/95732_ISOARD_2020_archivage.pdf