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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
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. Argument(ation) mining, the new and rapidly growing area of Natural Language Processing (NLP) and computational models of argument, aims at the automatic recognition of argument structures in large resources
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Agriculture: Natural Language Interfaces over Robotic and Analytical Farming Systems In the context of the MSCA JD project GreenFieldData https://www.eu4greenfielddata.eu/ GreenFieldData: IoRT Data Management
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close coordination with project partners, the recruited researcher will conduct experiments to determine the extent to which neural models, now at the heart of many approaches to Natural
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gas analysis, a GC/MS, and an HPLC/MS. DFT calculations will be performed using annual allocations on national high-performance computing centers. More details here: https://iramis.cea.fr/en/nimbe/lcmce
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to the understanding of physical mechanisms underlying these complex plasmas. The laboratory team has extensive experience in both experimental and modeling of this type of plasmas. Thus the candidate will have existing
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on electrophysiological approaches (MEEG, iEEG) and signal processing, while in Maastricht, the partner team provides ultra-high-field imaging (7T and 9.4T fMRI) and AI-based modeling. The PhD student will be enrolled
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Technologies INspiring Young scientists (DESTINY2, https://www.destiny-phd.eu/ ) is opening 24 doctoral positions hosted by universities, research centres, and laboratories in France (17), Spain (3), Germany (1
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the genesis of gravitational crises. These crises result in hundreds of landslides in a matter of days, as in January 2018, when more than 150 events were recorded in 48 hours. Conventional forecasting models
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with experimental groups that will study a physical realization of the qubit will be part of the project. Where to apply Website https://emploi.cnrs.fr/Candidat/Offre/UMR5798-FABPIS-015/Candidater.aspx