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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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start quickly and effectively, leveraging your experience in data analysis, machine learning and biomarkers quantification to contribute from the onset. You will liaise with external collaborators and
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with PhD and master students and with medical doctors. You will start quickly and effectively, leveraging your experience in data analysis, machine learning and biomarkers quantification to contribute
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machine learning tools. The postdoctoral fellow will contribute to various aspects of the project, such as: * developing new theoretical and numerical approaches for determining the thermodynamic and
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analysis, multi-omics analysis, differential analysis, machine learning methods. Definition of tasks to be performed: Fixed-term contract essential to carry out the bioinformatics part of the project
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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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. • Strong knowledge of signal processing methods and machine learning. • Familiarity with regulatory and ethical constraints in research involving sensitive data. • Ability to work closely with
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for model creation and operation Write scientific articles Supervisory duties Number of staff supervised Category C : 1 Ability to integrate into a project involving more than ten people Computer languages
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of the art data science approaches (text mining, machine learning, AI) to comprehensively highlight yet undiscovered virus/host/environment relationships and annotate potentially putative new spillover