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skills (one or more of the following strongly desired) Exploratory analysis of massive datasets (machine learning methods) Spatial data analysis and Geographic Information Systems (GIS) Forecasting and
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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
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Université Grenoble Alpes, laboratoire TIMC, équipe GMCAO | Grenoble, Rhone Alpes | France | 2 months ago
Post-doctoral Position In Medical Image Processing The Computer-Assisted Medical Interventions (CAMI) team at the TIMC laboratory (Grenoble, France) is seeking a highly motivated postdoctoral researcher
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Machine/Deep learning and classification Knowledge of the Linux operating system for using a computing cluster Interest in transdisciplinarity and teamwork Autonomy and scientific rigor Website
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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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Inria, the French national research institute for the digital sciences | Bures sur Yvette, le de France | France | about 2 months ago
mathematical modeling (preferably physiological systems) and/or control theory. -Experience in signal processing and artificial intelligence methods (time-series analysis, machine learning, multimodal
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 28 days ago
framework that maximizes sensitivity to the targeted model parameters. In addition, one could also study the separation of partial data, for instance using learning techniques. The applicant will review
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-criteria, defining their formalization as fuzzy subsets, and characterizing their uncertainty; Integrating Machine Learning algorithms to better account for low-level sensor data (precipitation, wind-driven
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be the continuation of previous work, would use machine learning on a simulated data base to define the tool, followed by an application to real data from GRAVITY/VLTI (K band), MATISSE/VLTI (L, M, N
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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