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of MIXAP on teaching and learning. We aim for a qualitative and quantitative analysis with questionnaires for teachers and students, focus groups, videos, usage logs, etc. • Provide a list of
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spoken and written is required The candidat must have a PhD in computer science, machine learning, or computational biology The position is available immediately and will remain open until filled
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computational framework, integrated with deep reinforcement learning (DRL) methodologies for both gene-level and edge-level perturbation control, represents a significant advancement in the computational toolkit
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Description of the offer : We are opening two positions in the field of “Metallic and Oxide Materials for Orbitronics and Magnonics” at Institut Néel, CNRS, Grenoble The first position (PhD
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Skills/Qualifications Strong background in Operating Systems and Linux development Knowledge of memory management mechanisms and system-level programming Experience with Machine Learning models (design
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experimental parameters (time, temperature). To optimize these parameters, active learning techniques based on Bayesian optimization will be applied. In situ or ex situ characterizations (FTIR, ¹¹B/¹H NMR, HP
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in Artificial Intelligence (Machine Learning and Statistics) at CentraleSupélec, · Joël Eymery, Head of the Nanostructures and Synchrotron Radiation Team at CEA Grenoble, · Jean-Sébastien
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. The post-doctoral researcher will work on an NWO/FNR-funded project. The project is a close collaboration with the laboratory of Alfred Vertegaal (Leiden University, Netherlands) and Anna Alemany (Leiden
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innovative methods for processing and analyzing 7Tesla MRI images of different modalities and formats (NIFTI, DICOM, etc.) using machine learning and artificial intelligence techniques. These methods will be
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) and Aurélien Quiquet from the Laboratoire des Sciences du Climat et Environnement (LSCE), an expert of the GRISLI model, in interaction with the PhD student on the ANR Delta project (coordinated by Y