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a modeling approach inspired by statistical physics to describe individual strategies, their interactions, and emergent effects at the group scale. The candidate will contribute to the development and
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to join the AI for Genome Interpretation (AI4GI) group at the IGMM (CNRS, Montpellier). The project is a collaboration between IGMM and IMAG, at the interface of genetics, bioinformatics, statistics
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models, assessing their effects on large-scale-structure (LSS) statistics as measured by the power spectrum and bispectrum of galaxies or intensity maps. The project emphasizes spectroscopic galaxy surveys
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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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FieldPhysicsEducation LevelPhD or equivalent LanguagesFRENCHLevelBasic Research FieldPhysicsYears of Research Experience1 - 4 Additional Information Eligibility criteria Statistical physics, active matter, biophysics
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ExperienceNone Additional Information Eligibility criteria • PhD in statistical genetics, bioinformatics, evolutionary genetics, or a related field (obtained or in progress) • Strong knowledge of statistical
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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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collaborate with ARCHIVES project partners to ensure coordinated progress and sharing of results. · Develop solutions combining numerical modeling, mathematical methods, and statistical/AI approaches
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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