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to characterize non-classical quantum states of light, and optimize processes to produce them. Context of the research topic and proposed workplan Non-classical (a.k.a. non-Gaussian) states of light like photon
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phenotypes • Analyze images and other data • Optimize induced pluripotent stem cell (iPSC) protocols • Disseminate and enhance research findings • Establish standard operating procedures (SOPs) This project is
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artificial intelligence, to optimize conditions. This project is funded under the Emergence@INC 2025 program (https://www.inc.cnrs.fr/fr/personne/yassine-kadmi ). -Development of a new, simple, rapid, and
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goal of this project is to design and optimize a novel adsorbent-electrode capable of simultaneously capturing and mineralizing PFAS in a sustainable one-pot process. - Synthesize and characterize
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and languages for application development and integration: Git, ROS, C++, Rust... - Solid background in estimation/filtering and optimization. - Fundamentals of robotics and perception. The aim
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candidate (M/F) will design organic-inorganic hybrids with lamellar structures containing one or more molecules of interest using environmentally friendly strategies, optimize the parameters governing
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Post-doctorate position (M/F) : Exascale Port of a 3D Sparse PIC Simulation Code for Plasma Modeling
to exascale architectures an initial 3D simulation code developed as part of previous work [1]. This work will initially focus on scaling up (distributed memory), optimizing CPU algorithms (vectorization) and
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students. It was heavily involved in various aspects of the experiment: analysis of the data collected by the prototype at CERN (ProtoDUNE), simulations and optimization of the neutrino event reconstruction
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Process: designing, preparing, shaping and characterizing materials in order to discover, control and optimize specific functions. The ICMCB carries out fundamental research on model materials and/or
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quantum dashes grown by droplet epitaxy [2]. We will explore the potentialities of this new approach to demonstrate the first monolithic tunable LC-PD and optimize its design and performances for FBG