23 phd-in-architecture-landscape-built-environment Postdoctoral positions at CNRS in France
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. Benefiting from a rich multidisciplinary environment, the team is hosted within the “RNA” research unit (CNRS unit 9002 “RNA Architecture and Reactivity”). This unit brings together 12 research groups (nearly
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, and scientific computing with complementary experimental activities, making it a natural setting for modelling‑led research on functional organic materials. IPREM provides a comprehensive environment
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well as their electrical characterisation. His/her role will involve overseeing all nanofabrication activities within the project, including the development of new cleanroom processes, as well as training PhD students in
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laboratory. Group publications on the topic Operando Investigation of Nanocrystal-based Device Energy Landscape: Seeing the Current Path, M. Cavallo, et al., Nano Res (2024). Operando Photoemission Imaging
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” focusing on the effect of a fluctuating environment on the collective dynamics of self-propelled agents, a numerical part on “reinforcement learning” focusing on optimizing communication between agents in a
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of Research ExperienceNone Additional Information Eligibility criteria - The applicant must have a PhD in physical chemistry, colloid science, soft matter physics or related fields of research - Skilled in
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-Marseille Université (AMU), CNRS and Centrale Marseille (ECM). The LMA employs around 110 people, including 70 permanent staff and some 40 PhD students/post-doctoral researcher. The LMA has nationally and
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charge of the IMN experimental part of the ANR BiBOP project on electron microscopy and XPS spectroscopy under controlled illumination and environments. Perform structural, physicochemical, and optical
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contracts and 102 doctoral students. This research activity will be carried out within the CMS team, which is right now composed of 12 permanent researchers, 4 PhD students, and 10 engineers. The recruited
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over the course of the project. References: - Deneu B et al (2021) Convolutional neural networks improve species distribution modelling by capturing the spatial structure of the environment. PLoS Comput