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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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machine learning approaches to integrate single cell and spatial analysis in order to identify molecular signatures and pathways underlying radiation-induced effects. Collaboration: Work in close
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single micro-sphere of frozen water. This bulkiness presents a significant limitation, and the emission has no directional control. This PhD thesis will build on a decade of research into novel laser
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of the art data science approaches (text mining, machine learning, AI) to comprehensively highlight yet undiscovered virus/host/environment relationships and annotate potentially putative new spillover
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visualization. Experience with GWAS, Bayesian modelling, and/or machine learning applied to biological data. Strong programming skills (R, Python) and ability to manage large-scale -omics datasets. Good
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). An overview of recent multi-view clustering. Neurocomputing, 402, 148-161. 7. Ji, Y., Lotfollahi, M., Wolf, F. A., & Theis, F. J. (2021). Machine learning for perturbational single-cell omics. Cell Systems, 12
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | 2 months ago
Emeraude INRIA/INSA-Lyon research team which is physically based at the CITI Lab of INSA-Lyon (Villeurbanne, France). This PhD will be conducted under the supervision of Romain Michon (Inria) and Pierre
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. The project proposes an innovative approach to model sea ice dynamics from the ice floe scale to the basin scale, leveraging hybrid data assimilation and machine learning methods to shape a physically robust
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Institut of Mathematics of Marseille | Marseille, Provence Alpes Cote d Azur | France | about 2 months ago
machine learning applications. Position Objective : The primary focus of this position is to develop concentration inequalities in the nonstationary setting, specifically for periodic Markov chains and
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of and experience with hydrological and/or hydrogeological modeling - Knowledge of and experience with AI concepts (machine learning, deep learning, and PINNS) and/or digital twin development - Experience