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Computational Mechanics. Solid background in continuum mechanics and numerical modeling Strong interest in machine learning and scientific computing Experience with numerical methods for PDEs and data-driven
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Computational Mechanics. Solid background in continuum mechanics and numerical modeling Strong interest in machine learning and scientific computing Experience with numerical methods for PDEs and data-driven
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 14 days ago
dynamics data and advanced graph-based deep learning models to decode long-range communication pathways within macromolecular complexes. The PhD candidate will play a central role in this effort by
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meters. These instruments produce large amounts of data that require several processing steps before the relevant physical variables are obtained. Typically, machine learning methods are used to optimize
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 14 days ago
Website https://jobs.inria.fr/public/classic/en/offres/2026-09928 Requirements Skills/Qualifications Profile: - The candidate is completing a Master's or engineering’s degree in Computer Vision, Electrical
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, SIAM Review, 60(3):550–591 (2018). [4] Diederik P Kingma and Max Welling, Auto-Encoding Variational Bayes, International Conference on Learning Representations (ICLR) 2014 ArXiv. http://arxiv.org/abs
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | about 1 month ago
the communication and storage needed to retain most of the information. Environment. The PhD will take place at Inria Grenoble, in the Thoth team. This is a large team focused on machine learning, and
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the "Machine Learning and Gene Regulation" team led by William Ritchie, specializing in bioinformatics and post-transcriptional regulation. The scientific environment at the IGH — international seminars, journal
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comprehensive platform for data extraction, analysis, and version control, providing access to highly curated datasets in a machine learning-friendly format. This PhD is part of the CARES project (Chemically
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Reflectometry The aim of the PhD project is to provide machine learning (ML) based neutron reflectometry (NR) analysis as an automatized workflow for the reflectometry instruments at the Institut Laue-Langevin