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-throughput high-resolution accurate mass-based metabolomic data and advanced AI analytics to efficiently mine and analyse LC-MS-based metabolomic data and to provide biological insight on the role of microbial
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multimodal metabolomics using LC-HRMS/MS, GC-MS/MS, and advanced NMR approaches. - **Activity 4:** Multivariate statistics and machine learning to identify microbial and chemical biomarkers of resilience
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characterization of magnetic nanoparticles • OncoProt – TBMCore: High-resolution quantitative proteomics and LC-MS/MS workflows • LaBRI (Bordeaux Computer Science Research Laboratory): Data science
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. - Experience in structural mass spectrometry, particularly HRMS, LC-MS, native MS, intact mass or top-down MS, would be highly desirable. - Experience in the characterization of monoclonal antibodies
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within the institute and provide access to state-of-the-art instrumentation, including NMR spectroscopy (300 and 500 MHz), mass spectrometry (LC-MS and HRMS), and X-ray diffraction. Synthesis of N
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allocated to the project will cover confocal microscopy experiments, LC-MS/MS proteomic analyses, RT-qPCR, RNA sequencing and analysis, as well as plant production and characterisation. It will also cover