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the development of high-reliability fiber components and optimized doped fibers. The first objective of this project is to explore different approaches to develop fluoride fiber components and build optical benches
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theory. The researcher will work in the G-SCOP laboratory, in the "Combinatorial Optimization" team, on geometric aspects of graph theory, in particular the links between structure and metric, and the
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Center for Immunology of Marseille-Luminy (CIML) | Marseille, Provence Alpes Cote d Azur | France | 5 days ago
of produced antibodies using high-throughput approaches Optimizing and standardizing library preparation protocols to ensure high-quality genomic data Collaborating with bioinformaticians to validate sequencing
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of sea turtles - Developing innovative machine learning methods to analyze the sounds associated with these behaviors - Automating the processing of audio and visual data to optimize the quantity and
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computational approaches to biological systems. Its core activity is the development of deep learning methods for protein design and optimization, with applications in biology and medicine. - activities: We
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optimization. Knowledge in algorithms for sampling/variational inference and kernel methods will also be welcome. Interest or experience in differential geometry, optimal transport, and remote sensing
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activity - Conducting catalytic tests (liquid-phase hydrogenation) - Interpreting results to understand reaction pathways and observed phenomena, and proposing practical and effective solutions to optimize
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, manufactured using a hybrid PIP (Polymer Impregnation & Pyrolysis) - CVI (Chemical Vapor Deposition) process from a ceramic fiber preform. This process requires optimization, whereby the structure of the porous
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the evaluation, the intensification and the optimization of carbonation (biotic and abiotic) processes involving different feedstocks, to address three different applications of industry decarbonation, in straight
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considerable. While advances in recent years have largely relied on pattern recognition models and optimization techniques to scale up, the emergence of generative models—whether based on diffusion models (score