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, statistics and scientific computing. * Proficiency in a scientific programming language, particularly Python, and the ability to develop reproducible processing procedures. * Knowledge of machine learning and
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, GC-MS/MS, and advanced NMR approaches. - **Activity 4:** Multivariate statistics and machine learning to identify microbial and chemical biomarkers of resilience and reveal the interactions linking
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to correlate polymerisation kinetics, macromolecular architecture, morphological evolution and drug encapsulation mechanisms. Beyond experimental work, the project will integrate machine learning approaches
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on developing deep learning methods for the reconstruction and physical analysis of ATLAS experiment data. The selected candidate will develop innovative analysis methods for the reconstruction and physical
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remaining biologically interpretable? The PhD candidate will design and apply integrative computational workflows using methods such as multi-omics integration, spatial modelling, representation learning
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on lncRNA structure. These experimental constraints will then be used to guide deep learning-assisted RNA 3D structure prediction tools, in order to generate ensembles of structural models. Clustering and
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data) will help validate observations and refine predictive models. Automated monitoring tools (scripts, dashboards, alerts) incorporating machine learning algorithms or statistical methods will be
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the SPIN Doctoral School (ed-spin.doctorat-bretagne.fr). Vincent Lebastard at IMT-Atl Nantes will co-supervised the PhD thesis. This thesis is part of the PEPR Acc Robotique MiniRo (https://anr.fr/fileadmin
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to apply Website https://emploi.cnrs.fr/Offres/CDD/UPR3228-SEVBOR-002/Default.aspx Requirements Research FieldPhysicsEducation LevelPhD or equivalent Research FieldPhysicsEducation LevelPhD
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to apply Website https://emploi.cnrs.fr/Offres/CDD/UMR8023-ANTSAI-004/Default.aspx Requirements Research FieldPhysicsEducation LevelPhD or equivalent LanguagesFRENCHLevelBasic Research FieldPhysicsYears