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experimental campaigns to acquire the data required for his thesis, as well as for the MONI-TREE project as a whole. The PhD will take place in LETG-Rennes, with expected missions to ONERA's Palaiseau for works
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-dimensional Euclidean spaces - Machine learning - Distributed computing - Complexity (communication, queries, memory) - Continuous optimization The specific topic can be refined based on the candidates' skills
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for battery electrodes), and potential key role in superlubrication. We will use a range of modelling techniques such as density functional theory, xTB, and potentially machine learning approaches. The project
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(Project IRP INANOMEP of the CNRS, France-Belgium). The synergy between non-linear optics, theoretical chemistry, and machine learning gives a pronounced interdisciplinary character to the project
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at EM2C lab, which consists in introducing virtual species and reactions whose thermodynamic and chemical properties are optimized by machine learning algorithms to retrieve properties of reference flames
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materials using online sensoring, machine learning and digital decision-making tools This PhD offer (PhD 13) is part of the 15 PhD contract proposals related to the European CESAREF project (www.cesaref.eu
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computing centers. The recruited person will have the opportunity to attend various training courses during her/his thesis, either related to the subject of the thesis or to more general topics. A PhD
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design, and innovative computer architectures. Our research interests range from the study of fundamental phenomena to the design of new devices with potential for technological applications in information
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computing techniques and machine learning approaches. In addition to the physics analysis, you will perform studies for extending the existing real-time analysis software running reconstruction and selection
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) based channel estimation algorithm can be designed and implemented by simulations in the framework of compressive sensing theory. Advanced machine learning techniques can also be investigated to serve