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a team More specifically: - For mission 1: knowledge of signal and image processing, machine learning (PyTorch or TensorFlow + NumPy/SciPy), statistical processing & data and results visualisation
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develop machine learning approaches (deep learning) to understand the eco-evolutionary mechanisms underlying biological diversity from environmental (phylo)genomic data. - Methodological developments in
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nervous system to modulate future aversive/nociceptive experiences (Merabet et al., in preparation). Notably, this effect participates in how flies learn the relative aversive value between aversive
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), whose objective is to extend the HLA-Epicheck model, originally developed within the framework of a PhD thesis, and to implement new deep learning approaches to assess donor–recipient compatibility in
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” focusing on the effect of a fluctuating environment on the collective dynamics of self-propelled agents, a numerical part on “reinforcement learning” focusing on optimizing communication between agents in a
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instruments and high throughput genomics that informs advanced numerical analysis methods (modeling, statistics, machine learning). Plankton encompasses all organisms roaming with marine currents. Those
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Deep learning models, and in particular large language
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tools capable of integrating, modeling and interpreting this wealth of information. It is in this context that artificial intelligence (AI) approaches, particularly deep learning, offer considerable
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on the development of deep learning methods for reconstruction and physics analysis of the ATLAS experiment data. The successful candidate will develop innovative analysis methods for the reconstruction or the physics
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, statistics, machine learning and deep learning. The project Motivation: Interpreting the genome means modeling the relationship between genotype and phenotype, which is the fundamental goal of biology