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) About the Project Deep learning models, and in particular large language models (LLMs), have demonstrated remarkable capabilities but remain limited by their heavy computational requirements, lack
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associated with phenotypic (biomechanical and metabolomics) traits. Estimate locus-specific effect sizes and quantifying genetically-driven phenotypic variations. Develop Bayesian models and/or deep learning
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research and excellent digital literacy Strong interest in historical data, machine learning, data visualization, or digital hermeneutics Strong communication skills in English and good knowledge of French
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Additional Information Eligibility criteria Transversal knowledge required : - Expertise in machine learning and deep learning in particular - Knowledge in ecology, marine biology, or oceanography would be a
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dimensional information, classification and/or deep learning methods may also be developed. In addition, the complementarity between the different data sources used (particularly between aerial LiDAR data and
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, Python, Bash). Good level on machine learning. Good level of written and oral English. Ease in a multidisciplinary environment, taste for teamwork, interpersonal skills. Scientific curiosity