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Laboratory's activities cover a wide range of fields, from statistical physics to hydrodynamic turbulence, including mathematical physics and signal processing, as well as soft and condensed matter
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experiments. Proficiency in data analysis, including statistical analysis. Team working and interest for multidisciplinary research. The candidate will be integrated into a young and dynamic team, composed
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hybrid electrodes (tetrodes & field potentials) in human data Perform the pre-processing, time-frequency analyses, statistical analyses and modelling necessary to link neural characteristics to decision
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of statistics. - Solid programming skills in Python and in scientific computing (PyTorch, scikit-learn, numpy, etc). - Familiarity with GNU/Linux. - Problem solving skills. - Good communication and teamwork
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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
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to carry out the following tasks: Development of analysis scripts for the preprocessing and automated processing of functional neuroimaging data; Statistical modeling of imaging data and evaluation
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applications, for example in machine learning and mathematical statistics Participation in the scientific activities of the department, e.g. seminars, workshops and schools organised by the members
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that incorporates a broad range of neutrino and dark-matter models, assessing their effects on large-scale-structure (LSS) statistics as measured by the power spectrum and bispectrum of galaxies or intensity maps
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, statistics, quantitative/qualitative analysis. - Appetite for educational AI, LLMs, or data analysis (advanced skills not required but appreciated). Cross-functional skills - Interdisciplinary teamwork
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biology We expect a candidate with a strong background in machine learning or statistics. The candidate must also be proficient in high-level languages like Python. Familiarity with single-cell date and