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collaboration with the University of Zurich. Mission The researcher will integrate, optimize, and stabilize the RNb-NeuS neural 3D reconstruction method within the AliceVision software architecture, enabling
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hydrogel-based biomimetic matrices (notably GelMA) to support the generation, maturation and functional optimization of multicellular adipose organoids, and integrate them into microfluidic platforms
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mechanistic features will be deciphered in order to fully understand the cleavage reaction of DNA with DNAzymes. Sample preparation (DNA both as catalyst and substrate), followed by optimization of pulsed EPR
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collaboration with the University of Zurich. Mission The researcher will integrate, optimize, and stabilize the RNb-NeuS neural 3D reconstruction method within the AliceVision software architecture, enabling
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description There is a need to develop optimized Mixed Matrix Membranes (MMMs) based on highly
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Two-year postdoc position (M/F) in signal processing and Monte Carlo methods applied to epidemiology
. To that aim, both Stein-based bilevel optimization, empirical Bayesian and unsupervised deep learning approaches will be considered. The recruited postdoc researcher will tackle both implementation challenges
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chemicals (e.g., HF). In this project, we propose to develop the synthesis of MXenes by chemical vapor deposition (CVD) and by using molten salts. The work at IS2M will consist of optimizing the synthesis
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of neuronal and vascular responses; Contributing to the instrumental development of the system (optimization of detection, illumination control, multi-camera synchronization); Analyzing and interpreting
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mapping their spin textures at the atomic scale using quantum magnetometry techniques. The work will also involve processing, analyzing, and interpreting STM/S data, contributing to instrumental development
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the most informative polarimetric parameters and optimal wavelengths for detecting abiotic stress. This approach will contribute to more accurate digital phenotyping, supporting sustainable crop monitoring