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to develop, optimize and apply advanced mass spectrometry approaches for the structural and molecular characterization of ARDCs, and to analyze and interpret the resulting data. - Develop and optimize mass
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | about 16 hours ago
initiative between two Inria research teams: Gamble (Inria Nancy) and Ouragan (Inria Paris), in collaboration with the ANR StratMesh project. The objective is to develop new methods and reliable visualization
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 16 hours ago
contribute to the design, development, and experimental validation of novel graybox tunneling algorithms for multi-objective combinatorial optimization, with a particular focus on their parallelization and
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for developing and optimizing plasma-based functionalization processes for ferrimagnetic nanoparticles. The successful candidate will be responsible for investigating the relationships between plasma parameters
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undergone in the murine model using an experimental influenza vaccine that has already been developed in our laboratory using antigens derived from the H1N1/PR8 influenza strain. Candidate profile: We
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Inria, the French national research institute for the digital sciences | Grenoble, Rhone Alpes | France | about 16 hours ago
in the development and maintenance of the PEPit (https://pepit.readthedocs.io/ ) software package, including adding functionalities related to parallel optimization, Implementation and benchmark
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, plays a central role in the development and promotion of chemical sciences in both research and education. Its activities are structured around two major transverse research themes (Environment and Health
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Is the Job related to staff position within a Research Infrastructure? No Offer Description The postdoctoral researcher will contribute to the development of new sensing functionalities based
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the transfer of heat, fluids, and gases from the mantle to the crust, crustal deformation and the evolution of sedimentary basins through flexural isostasy in response. However, these large-scale processes
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learning, epigenomic data, and mechanistic modelling. The mission is to contribute to the development of predictive models of the replication initiation probability landscape (IPLS) from limited experimental