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Field
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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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. 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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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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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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labeling accuracy as an intrinsic dimension of quality, resulting in structured and repeatable quality reports. Instantiate and validate the framework on several existing NIDS datasets (public datasets as
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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
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industrial partners. - Construction of electrochemical cells incorporating specially designed magnetic field sources, including quantitative measurement of local magnetic fields. - Implementation of tools