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to improve predictive performance and interpretability. By combining methodological innovation in AI with applications in human genetics, cancer genomics, and plant genomics, AI4GI aims to advance our
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the microstructure of these semi-crystalline polymers, alongside in-depth characterization to elucidate their structure-property relationships and enhance their performance in various energy-related applications
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of chemically storing and releasing hydrogen, using methanol as a reservoir. Main activities: • Utilize global optimization codes and perform DFT calculations on supercomputers. • Analyze results and
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, optimisation of chromatographic conditions, development of a comprehensive standards database) and will perform metabolomics studies in human, cellular and animal samples. He/She will contribute
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the project. Design and perform experiments to investigate lipid metabolism and organelle dynamics. • Apply cell biology, biochemical, and imaging approaches to study lipid synthesis, transport, and storage. • Develop
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experimental validation of mathematical and computational models linking individual microscopic dynamics, information propagation, and collective structures (norms, social networks, global performance
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the performance and sensitivity of a future space mission for cosmology. The candidate will be required to simulate the performance of a specific instrument using Python code in order to predict the sensitivity
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performance to address the challenge of detecting radioactive contaminants in liquids. The Institut Pluridisciplinaire Hubert CURIEN (IPHC), a joint research unit under the joint supervision of CNRS and the
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for nanometric ion implantation based on laser ionization of neutral atoms coupled to a focused ion beam (FIB). The researcher will take part in the design, implementation, and performance characterization
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that will remain present in this environment. Within the framework of this future organization, it is anticipated that the role of operators will increasingly shift away from performing often repetitive