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Domaine Mathématiques, information scientifique, logiciel Contrat Stage Intitulé de l'offre INTERNSHIP - Uncertainty Quantification for Material Science - 6 months - Saclay H/F Sujet de stage
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Domaine Mathématiques, information scientifique, logiciel Contrat Post-doctorat Intitulé de l'offre Cybersecurity formal analysis of fault-injection attacks in hardware/software embedded systems
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to support research. Implement algorithms, data structures, and other computational techniques to solve complex problems. Collaborate with cross-functional teams to integrate software components into larger
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Domaine Mathématiques, information scientifique, logiciel Contrat Post-doctorat Intitulé de l'offre Security Contract Semantics for Fault-Injection Attacks in Embedded Systems H/F Sujet de stage
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of advanced ML techniques, including Generative Adversarial Networks (GANs) for data augmentation, active learning for efficient simulation selection, and regression models for predictive analysis. The intern
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Category Mathematics, information, scientific, software Contract Internship Job title Improving the Effectiveness of LLM-Assisted ISS Generation from Design Specification H/F Subject The internship
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With the increasing complexity of numerical simulation codes, new approaches are required to analyze the ever-growing amount of data. This requires coupling up-to-date data analysis libraries with
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nanofabrication, cryogenic experiments, experiment control and data acquisition. Strong python programming knowledge is a clear asset. French language proficiency is not necessary. The candidate will work within a
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information (e.g., semantics) for the intended goal of communication. An end-to-end evaluation is fundamental to assess the positive and negative impacts of in-network AI. In this direction, the project has a
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systems [1]. Prototype cells already available in the lab may be used and incrementally modified to gather preliminary data on limitations, artefacts and reproducibility. The newly developed test cell