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rely on the development of models integrating different data sources, initially based on data simulations, consistent with the data sets that are actually available or planned for acquisition, as
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solutions for integrating multiple biological modalities and to establish a link between the phenotype observed under the microscope and various molecular measurements of the cell. The methods will be
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? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description As a member of the LAM's Research and Development group, your mission will be
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represents a model for research on HIV-cure (i.e., spontaneous control by the immune system, allowing anti-retroviral treatment interruption). Plasmacytoid dendritic cells (pDC) are central to the difference
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language models to whole genome sequencing data - Develop algorithms and neural network architectures for the prediction of structured outputs (i.e. trees, graphs) - Implement and develop methods
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the framework of the PEPR Sous-Sol project ORGMET conducted by a consortium of four French laboratories GET, INEEL/ESRF, LFCR and IPREM (https://www.soussol-bien-commun.fr/fr/appel-projets-2024/orgmet
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to communicate effectively and work in a team. • Enthusiasm for studying virus evolution. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UPR9022-BENSTE-057/Default.aspx Work Location(s
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) is required. More generally, we are looking for an open-minded candidate with an interest in the ecology and evolution of emerging pathogens. Website for additional job details https://emploi.cnrs.fr
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conditions such as cancer, yet the underlying mechanisms remain poorly understood. Understanding how disruptions in these processes contribute to cancer development and cell fate decisions is a central
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modeling with deep learning for the analysis of hyperspectral imaging data. The researcher will be responsible for the design and development of numerical models, including neural network architectures