Sort by
Refine Your Search
-
5 Sep 2026 Job Information Organisation/Company CNRS Department Laboratoire d'Informatique, Signaux et Systèmes de Sophia Antipolis Research Field Engineering Computer science Mathematics Researcher
-
): the doctoral candidate will work to SAFRAN's site in Colombes (France). Objectives This PhD project aims to investigate the influence of ceramic shell microstructure and cluster architecture on the thermal shock
-
advanced NMR methodologies, the project aims to provide unprecedented insights into the architecture and remodeling of this essential cellular structure at the atomic scale. Where to apply Website https
-
for Systems Analysis and Architecture (LAAS) within the MechaBioFluidics team, which has extensive expertise in microfluidics and microfabrication (a technology platform of the national ReNaTech network), in
-
1 Aug 2026 Job Information Organisation/Company CNRS Department Institut de recherche sur les céramiques Research Field Chemistry Physics Technology Researcher Profile First Stage Researcher (R1
-
meetings and scientific quality control. • Supervise fine-resolution stratigraphic excavation, the definition of stratigraphic units and loci, architectural recording, interface documentation and site
-
the context of a PEPR project, in collaboration with eight CNRS and CEA laboratories working on the future of electrical grids. More specifically, it is linked to WP5, dedicated to cybersecurity and network
-
printable internal architectures, and we will experimentally test these new shape-changing materials (3D scanning, mechanical testing). https://blog.espci.fr/benoitroman/phd-position-depressure-activated-pro
-
intelligence. It promotes strong Franco-Canadian collaborations and offers an ideal framework for hardware–algorithm co-design projects. The scientific organization of the PhD project will rely on close
-
technologies generate large volumes of heterogeneous data and often require advanced technical expertise to operate, configure, and interpret. This PhD project will explore how Large Language Models, Natural