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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 3 months ago
for final-year Master’s students or engineering school students with an interest in combinatorial optimization, constraint programming, and stochastic heuristics. The project will be carried out within
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of both the filament and the substrate, pressure, gas phase precursor composition) with the film chemical structure and the resulting optical properties will be carried out. The DC candidate will be trained
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measurements under electrochemical control. By combining plasmon-enhanced vibrational spectroscopy (SEIRA/SERS) with electrochemistry, the project seeks to elucidate structure–function relationships in redox
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of the data in order to decode the mode of action of NPPs in the context of mammary tumorigenesis. The doctoral research program is structured around two integrated research axes: Axis 1: Colloidal
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IFREMER - Institut Français de Recherche pour l'Exploitation de la MER | Nantes, Pays de la Loire | France | about 1 month ago
General for Maritime Affairs, Fisheries and Aquaculture (DGAMPA) are involved in co-construction workshops with stakeholders. The PhD candidate will join a dynamic research unit, DECOD, and will benefit
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and optimization of metasurfaces exhibiting tailored spectral responses at selected near-infrared wavelengths • Development of angularly robust optical functionalities over wide ranges of incidence
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testing of concrete structures Good Knowledge of data science, e.g. optimization, machine learning, and structural sensing technologies Openness to interdisciplinary research and commitment to teamwork
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a Research Infrastructure? No Offer Description Structure & Research environment The candidate will join the TREX laboratory (Translational Research and Experimental Corneal Surgery) at the Hôpital
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necessary to robustly extract the various constituent elements of the comic book (detection of panels and speech bubbles, text recognition, segmentation, and character identification), and then to structure
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(ILL). The current ML models are optimized mainly for (monochromatic) X-ray reflectometry. We aim to generalize this approach to a wide range of samples and time-of-flight NR, coupled with automatic data