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Field
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high level programs based on scientific instrumentation. The IPHC is structured into 4 departments and has a total staff of 393 staff including 257 permanent staff (ie 119 researchers and teachers
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implement machine learning models dedicated to the prediction, interpretation, and quantitative analysis of Raman vibrational spectra, establishing explicit links between structure, local chemical environment
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. Improved conceptual understanding of the mechanisms underlying soil structural and functional recovery under compaction, as well as factors influencing plant tolerance to compacted conditions. Contributions
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that seeks to link material structure, transformation processes, performance properties (mechanical, thermal, fire resistance, absorption, etc.), and their evolution throughout the product lifecycle
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cells to developing novel approaches to 3D molecular structure determination to understanding how viruses hijack a cell’s machinery and alter its metabolome, the researchers in Biochemistry and Molecular
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and département level) containing a range of socio-economic indicators (indices of location, specialisation, density, structure of the working population, etc.) and to integrate into them the effects
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research, CRISPR technologies, novel humanized mouse models of neuromuscular disorders and state-of-the-art delivery technologies for nucleic acid therapeutics, as well as research on disease mechanisms (see
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identity and extracellular signaling, but how cell types, signaling mechanisms, and transcription factors jointly determine tissue structure is incompletely understood. The Koplev lab is recruiting
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-ray tomography analysis - Knowledge of the hydro-mechanical behavior of raw earth - Mechanical characterization of materials and structures - Physical characterization of materials - Material
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Postdoctoral Positions for Computational Genomics, Cancer Genetics, and Translational Cancer Biology
mechanism-driven AI and agentic AI frameworks (iGenSig-AI, G2K) that integrate biological knowledge with cutting-edge machine learning to transform omics data into actionable therapeutic insights