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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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, 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. Achieving
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difficult to couple with basin simulators. Geochemical metamodels, particularly those based on machine learning, can significantly reduce computation times while maintaining physico-chemical consistency
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dynamical systems), epidemiological modelling, data analysis (statistics, machine learning). • in scientific programming (preferably Python, Matlab, R) Genuine interest in the analysis and modeling
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Post-doctoral Researcher in Multimodal Foundation Models for Brain Cancer & Neuro-degenerative Disea
Qualifications PhD in machine learning, computer vision or a related field. Established expertise in deep learning methods applied to images analysis. Experiences with generative models, volumetric image
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, etc.) Knows-how: • Design, implement, and evaluate machine learning and deep learning models, including multimodal architectures • Process, clean, and integrate heterogeneous datasets (electrical
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 16 days ago
that diffusion models are a fundamental divergence from traditional deep learning paradigms. This suggests that existing generalisation theories are insufficient and highlights the need for a bespoke, algorithm
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 13 days ago
biology. The team is growing and offers a highly interdisciplinary environment that brings together researchers in structural bioinformatics, computational chemistry, biophysics, and machine learning. We
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projects that rely on computational modeling and machine learning approaches. The postdoc will help bring these projects to completion, carry out the required validations, and take the lead in preparing
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, involving expertise in optics, electronics, image and data processing, chemistry, and biology. With the support of several European funding programs, the team is building a data science and machine learning