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to fundamental research in condensed matter physics, enriched by interdisciplinary activities at the interfaces with chemistry, engineering, and biology. The PhD student will join the Quantum Nano Electronics and
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PhD on 2D quantum photonics : towards neuromorphic applications with 2D ferroelectrics materials M/F
-of-plane ferroelectric domains. The goal of this PhD is to optically detect, track, and ultimately control the ferroelectric state in such materials. Key objectives include imaging ferroelectric domains in a
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value-added materials. Objectives of the PhD The PhD candidate will focus on designing and optimizing green spinning processes for lignin-based fibers, relying exclusively on enzymes and water, avoiding
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to develop chiral metal nanoclusters, understand their chirality at the atomic level through a combination of advanced spectroscopic techniques and theoretical simulations, and apply them to relevant processes
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join our team at IETR Laboratory, CNRS, Rennes, France for a fully funded PhD (3 years). The project is supported by the French National Research Agency (ANR) and Swiss National Science Foundation (SNF
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geographically dependent fossilized-birth-death model. 3) To enhance spatial birth-death processes such that speciation, extinction, fossilization and dispersal events emerge from population level dynamics
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research suggests that changes in metabolism, particularly lipid processing, may also play a key role in their development. The thesis project will explore the relationship between immune activation and
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- SOI) technology have shown to be excellent candidates for cryogenic temperature operation. Building on our previous studies and most recent results, the goal of this PhD is to implement microelectronic
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system serving a highly stable Mach-Zehnder interferometer, a state-of-the-art velocity map imaging (VMI) spectrometer, and an electron time-of-flight spectrometer. The position provides rigorous training
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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