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a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The postdoctoral researcher will contribute to the development of AI-assisted automated
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during a doctoral dissertation completed within the laboratory and the INNO-REV[1] project. Its objective is to develop and validate innovative passive techniques for improving the performance of latent
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oxides, we will first develop and benchmark machine-learning interaction potentials of increasing complexity. Subsequently, we will deploy a combination of brute-force and rare-event sampling to isolate
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with chromatin by recognizing acetylated lysine residues in histones. We previously identified these domains as promising targets for antifungal drug development [refs. 1,2]. More recently, we found
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consist in the development and use of new magnetization probes for the pulsed magnetic fields generated at the LNCMI-Toulouse. With this new setup, magnetization experiments will be performed on quantum
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to the development of primary, secondary and tertiary prevention. The EpiAgeing team (https://cress-umr1153.fr/index.php/epiageing/ ), comprises around 25 persons including researchers, clinicians, statisticians, post
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the CARNOT HyLBM project, which aims to develop advanced numerical models for hydrogen storage in nanostructured metal hydride reactors. The researcher will contribute to the development of advanced
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
. Assignments: With the help of Jeremie Dequidt (WP3 leader, Inria DEFROST team) and the WP3/T3.3 consortium partners, the recruited person will be taken to design, develop and validate the control software
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on a Carnot project dedicated to the development of air-stable solid electrolytes for Li-ion batteries to further facilitate their practical implementation. The project suggests chemical modification
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collaborations to implement cosmological analyses derived from the observation of Type Ia Supernovae. This work, carried out within the framework of the ANR SCINF project, aims to develop inference methods based