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biology • Multi-omics data integration and analysis • Pharmacogenomics and computational drug discovery • Pharmacogenomics and precision medicine • AI and machine learning applications in biomedical
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analysis, based on particle-in-cell (PIC) simulations, in order to (1) compare the effect of different types of broadband sources on the growth and saturation of three-wave coupling instabilities (Raman and
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performance simulation, lifecycle assessment, or climate resilience. Knowledge of uncertainty quantification and risk modelling is desirable. You have experience with programming and data analysis (e.g., Python
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, network-based analysis, unsupervised learning and interpretable AI. The project leaves room for methodological exploration while remaining closely connected to biological interpretation, experimental
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within the project Spa Research Centre. implementation of research activities, collection and evaluation of data in the field of socio-economic sciences, analysis and interpretation of research data
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matter in non-equilibrium conditions, defining new observables, and applying data-driven analysis to distinguish coherent response from fluctuations, correlations and phase-transition dynamics. Main tasks
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bioinformatic/biostatistical analysis (CNRS UMR8265, NeuroSU - IBPS - SU). It will benefit from a collaboration with O. Saulnier (0000-0003-4111-1017) a team leader at Curie Institute with expertise in
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energy Risk analysis Life cycle assessment (LCA) and modeling Should one or two of these components be lacking, it is nonetheless possible to supplement the knowledge base after the admission. Great
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Inria, the French national research institute for the digital sciences | Sophia Antipolis, Provence Alpes Cote d Azur | France | 3 months ago
on this topic, implement and test prototypes, and prepare scientific communications. Research activities, namely: Literature review Prototyping and experimentation Analysis of results Communication Where to apply
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. Developing sample preparation and MS/MS analytical protocols, Qualitative and statistical analysis of data. Preparing reports using data science notebooks, MS Word, MS PowerPoint etc. The Researcher will train