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which currently consists of 5 permanent researchers, 2 PhD students, 2 postdoctoral researchers. The PhD studies will be performed in the experimental rooms of the propulsion team at LPP in Palaiseau
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done to explore the effect of these defects on the multiphysical behavior of composites in cryogenic environments. The thesis topic is structured into three main parts. • The first part focuses
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join an interdisciplinary team and will be directly supervised by Fanny Cazettes (CNRS). This PhD project offers the opportunity to participate in an interdisciplinary research project aimed
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adult brains. These cells reside in tightly controlled microenvironments called “niches.” Objectives of the PhD project: The gestation and maternity periods in mammals open a window of important brain
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the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description At ICMUB, PhD
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evaluated annually by an individual PhD advisory committee. As the global population continues to age, age-related visual impairments are becoming a major public health issue. Vision plays a central role in
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how the brain adapts to a changing environment and how internal states modulate these processes. This PhD project focuses specifically on the computational aspect of this research. The successful
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Offer Description The work will be performed in the team Cascales (https://www.cascaleslab.fr ) of the Laboratoire d'Ingénierie des Systèmes Macromoléculaires (LISM). It is a joint PhD fellowship between
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10 Oct 2025 Job Information Organisation/Company CNRS Department Institut de Combustion, Aérothermique, Réactivité et Environnement Research Field Engineering Chemistry Physics Researcher Profile First Stage Researcher (R1) Country France Application Deadline 30 Oct 2025 - 23:59 (UTC) Type of...
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, Communication, Optimization • SyRI: Robotic Systems in Interaction The PhD student will join the CID team, whose research focuses on Artificial Intelligence, including statistical learning, uncertainty management