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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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activities between IETR and the French space agency CNES (https://cnes.fr ). This interdisciplinary project will be carried out at IETR – UMR CNRS 6164 (http://www.ietr.fr ) and it will strongly involve two
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the conditions of their formation as well as their structure and stability. The transformation or formation of extra species during oxidative water treatment processes will be studied varying different parameters
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composites (rheology, DMA, tensile testing, etc.) will then be studied in order to establish structure–property relationships. This work will be carried out within the Chemistry & Macromolecular Materials
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. The LPP is structured around three thematic research pillars: space plasmas, low-temperature plasmas (cold plasmas), and fusion plasmas. The Space Plasma group includes about 29 permanent researchers and
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techniques available at the IRCELYON and IFPEN laboratories. - Catalyst synthesis - Characterization of surface structure and reactivity, acid-base properties - Catalytic tests on model reactions - Kinetic
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producing PU dispersions from polyols synthesised from recycled waste cooking oils and optimising the formulations for applications such as varnishes and paints for the construction industry. - Development
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language models to whole genome sequencing data - Develop algorithms and neural network architectures for the prediction of structured outputs (i.e. trees, graphs) - Implement and develop methods
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screening. - Put the pipeline into production and test it on research topics from the laboratory and a collaborating team. The research will be conducted at the Molecular Microbiology and Structural
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existing structural and functional MRI data, acquire new data in collaboration with clinical researchers, and prepare publications and conference presentations. - Study preparation - Data acquisition (MRI