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on representation stability, interpretability, and efficiency.Despite their success, self-supervised approaches and foundation models still lack a thorough theoretical understanding. This project aims to bridge
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> Entity/Department: 3IA Côte d’Azur Institute •Open to: External applicants (contract position) •Contract duration: 2-year fixed-term contract •Category: A – Gross salary up to €3,200/month depending on experience •Job location: Teaching and training duties on the different campuses of...
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observed in Drosophila larvae. This interdisciplinary project combines biology, neuroscience, and computational modelling to understand how the larva’s body’s physical properties influence its motor control
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Wikibase instance Curate and model historical migration datasets within the dedicated Wikibase instance Contribute to the design of ontologies and metadata schemas for the knowledge graph Develop data-driven
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. In particular, the research project will focus on inferring trajectories from spatial transcriptomics data modelling at the same time the cells evolution in gene expression and in space. Required
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, traditional risk prediction models like the Steno Type 1 Risk Engine fail to account for the immunological dysregulation inherent in T1D. Project Objective The PhD candidate will primarily focus on the clinical
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innovative research utilizing wet-lab techniques, 3D models, and extracellular vesicles to advance our understanding of drug resistance in melanoma. Your responsibilities: Conduct wet-lab research in melanoma
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. To do this, knowledge or willingness to be trained in advanced statistical modelling, ideally with an interest in methods for causal inference in observational data, is strongly preferred. Using various
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and in pathological models, we aim to establish direct links between molecular determinants and muscle physiopathology Detailed Description of the Project : Not all muscles in the body are equivalent
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more (for an overview of these technologies, see http://behaverse.org/ ). Your role in this team will be to develop computational models and data analysis code to process large, multimodal behavioral