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methodology includes theory, modeling, instrumentation, and data analysis. For national and global scenario, climate resilience by assessing, monitoring, and predicting the current and potential climate change
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generative AI, foundation models (multi-modal LLM) and their major application fields (multimedia analysis, biology, etc.). Site internet : https://univ-cotedazur.fr/efelia-cote-dazur Description
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, (6) Metal and inorganic materials, (7) Organic materials, (8) Biomaterials, (9) Data-driven materials development, and (10) Advanced materials analysis technology. Internationally highly esteemed
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: (1) hydrogen-related materials, (2) battery materials, (3) quantum materials, (4) semiconducting materials, (5) artificial intelligence materials, (6) metal and inorganic materials, (7) organic
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) Artificial intelligence materials, (6) Metal and inorganic materials, (7) Organic materials, (8) Biomaterials, (9) Data-driven materials development, and (10) Advanced materials analysis technology. Highly
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will be given to research into (1) Hydrogen-related materials, (2) Battery materials, (3) Quantum materials, (4) Semiconducting materials, (5) Artificial intelligence materials, (6) Metal and inorganic
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of applicant to the publication, number of citations, impact factor of the journal), h-index, monographs, participation in international conferences (outlining the invited lectures), patents, projects
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Mathematics (including Physical Mathematics) especially in Analysis, Algebra and Algebraic Geometry, Applied and Applicable Mathematics and Statistics are encouraged to apply. In particular, applicants
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analysis (strain identification) and mass spectrometry (metabolite measurement) to obtain a microbial metabolism catalog. Advanced microscopy and high-content flow cytometry utilizing AI and multimodal
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-departmental teams to plan and execute events effectively. · Analyze the impact and effectiveness of events and adapt accordingly. Data Analysis and Forecasting · Regularly analyze relationship engagement