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POSTDOC (M/F) - Modeling and Analysis of Prospective Scenarios for Hydrogen in France and Germany The use of hydrogen produced by electrolysis, along with its derivatives (such as synthetic methanol
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The successful candidate will be responsible for: 1. Develop the numerical and analytical tools required to design these tunable random architectures and predict the mechanical behavior of the resulting metamaterials (elastic moduli, yield strength, toughness). 2. Use these tools to...
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signal conditioning inside a Li-ion battery cell. In the new field of the Reference Electrode (RE) insertion inside the Li-ion cells, the PostDoc will focus on the pre-conditioning electronics necessary
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29 Aug 2025 Job Information Organisation/Company CEA Department IRAMIS Research Field Chemistry » Analytical chemistry Researcher Profile First Stage Researcher (R1) Positions Postdoc Positions
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collaboration with other CEA teams, notably ; * Parallel and cluster computing environment and efficient LP/MILP algorithms for our large-scale models ; * Data structuring and storage solutions for model input
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resources to carry out your assignments. YOUR ASSIGNMENTS: The internship will develop and implement scalable, high‑performance algorithms for transient Lindblad dynamics tailored to the multi‑level Rydberg
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following areas: * Global economic analysis of long-term investment pathways , including the distribution of decarbonization effort across sectors and regions * Policy evaluation of global and sectoral
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29 Aug 2025 Job Information Organisation/Company CEA Department I-Tésé Research Field Economics » Environmental economics Researcher Profile First Stage Researcher (R1) Positions Postdoc Positions
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postdoc to pioneer next-generation thermal transport experiments on the micro-nano scale at École Polytechnique, France. Why This Position Is Exciting High-temperature superconductivity and quantum spin
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Aggregation [9], DP-SGD [10]. Analyze trade-offs between privacy and robustness in different scenarios, including non-i.i.d. data distributions. [1] Zhu et al. Deep Leakage from Gradients. NeurIPS 2019. [2