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] Cross, E. J., Gibson, S. J., Jones, M. R., Pitchforth, D. J., Zhang, S., & Rogers, T. J. (2021). Physics-informed machine learning for structural health monitoring. Structural health monitoring based
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is planned. Marianne Boix will also be co-advisor for the project. To develop the project, it is necessary to provide the PhD student with adequate computer equipment. 1.5 Interdisciplinarity aspects
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advanced seismic methods (including array processing, machine learning, and potentially distributed acoustic sensing) to develop novel approaches for monitoring unsteady and non-uniform flood flows across
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École nationale des ponts et chaussées | Champs sur Marne, le de France | France | about 2 months ago
authorities. École des Ponts ParisTech, in accordance with its strategic plan, develops a long-term research activity in the field of Machine Learning and Computer Vision. The IMAGINE team is a renowned
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psychological theory, cultural history, and interdisciplinary research. Good academic writing and communication skills in English. Desirable skills Knowledge of machine learning or advanced NLP techniques (e.g
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Microelectronics teams, the PhD student will be supervised and helped. He/She will access, after training, the IEMN technological platforms. He/She will be provided the tools and computer accesses necessary
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frequent cloud contamination. This scale mismatch prevents a coherent representation of radiative–thermal processes at the urban scale. This PhD will develop physics-informed deep learning models for data
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for Artificial Intelligence. https://miai.univ-grenoble-alpes.fr/ Activities Develop and evaluate deep learning tools for MRI fingerprint data Write scientific articles Present results at international conferences
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, machine learning and turbulence modeling. The researcher must hold a Phd in fluid mechanics / Applied mathematic / Machine Learning. Website for additional job details https://emploi.cnrs.fr/Offres/CDD
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articles, - Participating in conferences, - Supervising the writing of reports and articles by supervised students, - Supervising and training interns and PhD students. • Cross-functional tasks - Participate