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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 19 days ago
expertise of both supervisors. - Designing new efficient methods: To account for the structure of physic simulations, we propose to investi- gate how to efficiently leverage the inter-node communication
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these conditions have long been studied from a purely structural or mechanical perspective, increasing evidence highlights the crucial role of systemic and environmental factors in disease progression. Among
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aerosol layer, for example by injecting gaseous SO2 into the stratosphere, which then transforms into sulphate aerosols. Variations in this aerosol layer can alter the stratospheric thermal structure and
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to access novel structures and reactivities. Targeted applications include "green" catalysis, the design of smart materials (magnetic, optoelectronic ), and surface functionalization. An innovative aspect
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City Montpellier Website http://www.umontpellier.fr/ Street 163 rue Auguste Broussonnet Postal Code 34000 E-Mail frederic.cuisinier@umontpellier.fr STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn
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Additional Information Website for additional job details https://www.ietr.fr/en/techno-economic-studies-grid-capacity-allocations-future… Work Location(s) Number of offers available1Company
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material for an intended structural application. To conduct this study, a nickel-based superalloy (Inconel 718) will be used as a model material because of its broad industrial applicability and its
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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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The expert will participate in the necessary methodological developments and analyses of airborne data recorded by the IAGOS research infrastructure (https://www.iagos.org ) and from other networks, to provide
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Starrydata2). The work will include the implementation of machine learning models (neural networks, random forests, SISSO), generative approaches for predicting crystal structures, the use of machine learning