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perception for robotics; machine learning. o An interest for approaches based on foundation models. o Proficiency in open-source libraries: Pytorch or equivalent, OpenCV, Open3D, PCL, etc. o Programming
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relevant to the project's theme and activities. Solid experience in molecular simulation and/or machine learning is required, along with a good knowledge of associated theoretical tools (experience in
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on food craving and health-related decision-making. To this purpose, we will use a combination of brain imaging, behavioral measures, and machine-learning techniques. Activities The successful candidate
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that interaction represents the foundation of active learning and fosters acquisition and retention of knowledge, as opposed to passive reception in traditional teaching. Some benefits of MR are now well established
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, clustering analyses, propagating location and other uncertainties...) of mid-ocean ridge catalogs, using standard, Bayesian and machine learning techniques. ⁃ Implement methodologies that improve estimates
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instruments and high throughput genomics that informs advanced numerical analysis methods (modeling, statistics, machine learning). Plankton encompasses all organisms roaming with marine currents. Those
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). An overview of recent multi-view clustering. Neurocomputing, 402, 148-161. 7. Ji, Y., Lotfollahi, M., Wolf, F. A., & Theis, F. J. (2021). Machine learning for perturbational single-cell omics. Cell Systems, 12
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analysis and visualization, signal processing, and ideally machine learning. • Working knowledge of Distributed Acoustic Sensing (DAS) and its applications in seismology (appreciated). • Aptitude
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in the Earth's outer core, with implications for deep Earth processes [1]. A variety of inverse methods (data assimilation, machine learning, etc.) has been employed to recover the fluid motions in