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new pollen analysis • Modeling and Statistics: Utilize GIS, R statistical environment, and other tools for pollen-based modeling (REVEALS and LOVE models) and statistical analysis. • Collaboration: Work
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degree in aquatic microbial ecology and experience in high-throughput sequencing data analysis and statistical tools (familiarity with the UNIX terminal environment; management of big data on clusters
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- Programming skills (e.g., Python, Matlab) - Advanced knowledge of statistical analysis (e.g., R) Desirable skills: -Specialization in language development, including research experience with infants and/or
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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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statistical models. Within the Polarity, Division and Morphogenesis team, the candidate will work closely with biologists and physicists to develop approaches integrating spatial transcriptomics, cell dynamics
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skills in quantitative methods, statistics, and project management. Experience in dietary decision-making, eating disorders, or addiction/craving is considered a bonus. Additional comments -- Website
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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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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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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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FieldPhysicsEducation LevelPhD or equivalent LanguagesFRENCHLevelBasic Research FieldPhysicsYears of Research Experience1 - 4 Additional Information Eligibility criteria Statistical physics, active matter, biophysics