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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 7 days ago
2026). Antoine Boutet , Associate Professor at INSA Lyon. Ulrich Aïvodji , Assistant Professor at ÉTS Montreal. The PhD project will contribute to the core objectives of RAIDAC+, with a particular focus
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pathogenic lifestyles. OBJECTIVES: The key research objectives of this project are: • Annotating the B. fragilis transcriptome and sRNAs expressed during colonisation of host epithelial cells: Using
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. Bonus lectures can be picked by the students depending on their interests and project-specific requirements. Students can deepen their knowledge about selected topics (e.g. Bayesian Statistics, HMMs, AI
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Bayesian inference framework for identifying complex aerospace systems combining with limited experimental data. It can be also used to quantify uncertainties from experimental testing, significantly
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value-added materials. Objectives of the PhD The PhD candidate will focus on designing and optimizing green spinning processes for lignin-based fibers, relying exclusively on enzymes and water, avoiding
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objectives will also be prepared in French or English. Previous experience with Drosophila and confocal imaging would be an asset. Applicants are kindly asked to provide a complete CV along with the contact
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the position may begin as late as June 2026, upon request. The duration of the position is 4 years. Your tasks include: Conduct research in line with the research project objectives. Write high-quality research
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understanding of the role of forests in the water cycle. Objectives of the research: Study temporal patterns of climate and water-source related processes using stable water isotope chronologies from tree rings
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, to characterize immune cell dynamics in murine models of inflammation and cancer. RESPONSIBILITIES: Developing and performing computer simulation of MRI contrast of labelled cells and tissue Labeling and tracking
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networks, ensemble algorithms, and other advanced architectures, the objective will be to accurately predict the state of health (SoH) of batteries in the short, medium, and long term, including under