622 structures "https:" "https:" "https:" "https:" "https:" "Imperial College London" positions at CNRS in France
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at CRHEA (Valbonne, 06). It will focus on the epitaxy of these new structures using MBE and MOVPE techniques and their structural and electrical characterizations which will be validated by the partners
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. Argument(ation) mining, the new and rapidly growing area of Natural Language Processing (NLP) and computational models of argument, aims at the automatic recognition of argument structures in large resources
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, energy, transportation, and construction. The laboratory focuses on describing the relationships between processing, microstructure, and properties, using both experimental and modeling/simulation
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experimental, analytical, and computational platforms to support the project. https://www.get.omp.eu/ The work carried out during this post-doctoral contract will be integrated into the ERC StG LEAPHY project
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on isolated mutations in patients with telomeric disorders Construction of KI cell lines using CRISPR-Cas9 Characterization of the telomeric phenotypes of these KI lines Characterization of the phenotypes
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, or highlights certain sound sources in complex scenes, and determining how these processes are modulated by context (noise, multiple sources, attention). Where to apply Website https://emploi.cnrs.fr/Candidat
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. Postdoctoral researchers will have access to state-of-the-art imaging and cellular biology platforms, as well as a dynamic international research environment. Where to apply Website https://emploi.cnrs.fr
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chemistry synthesis (organic and coordination chemistry) - intercalation and exfoliation chemistry - synthesis in supercritical media - structural and spectroscopic characterisation - magnetic and
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allows for the precise design of quantum dots while retaining the exceptional mechanical properties of graphene. The electronic structure of bilayer graphene has been intensively studied in recent years
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of results at conferences - interaction with team members and international collaborators The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning