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Inria, the French national research institute for the digital sciences | Montpellier, Languedoc Roussillon | France | 3 months ago
postdoctoral researcher to work on the interpretability and explainability of Vision-Language Models (VLMs) for remote sensing applications, with a specific focus on Sentinel-2 data. This research aims
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://www.ige-grenoble.fr/-C2H-Climate-Cryosphere-and- Activities Improvement of algorithms for estimating geophysical quantities from remote sensing observations Management of ESA projects (collaborations
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for remote sensing data analysis.- Satellite image time series processing.- Oral and written communication in English and French. Savoir faire technique : - Working in Linux OS and HPC. - Advanced python
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area Travel to Nîmes (the model city) is to be expected. Knowledge of statistical analysis and modelling, analysis of complex networks, statistical mechanics Knowledge of R, Qgis, GIS software and
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with mouse models of infection will be appreciated. We are looking for strongly motivated and highly collaborative candidates having good communication skills in English and a sense of team spirit
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: - Hold a PhD in Geography, Agronomy, Ecology, or Computer Science. - Expertise in spatial modeling and foresight analysis applied to social and environmental sciences. - Theoretical knowledge in land use
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SLICES-FR research infrastructure- Communicate results through presentations, conference papers, and project reportsProfile and skillsThe R&D Engineer must already hold a PhD degree in Computer
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electrochemical transistors as sensing platforms. The researcher will be responsible for: o Architectural study of a passive backscatter communication system tailored for implantable biosensors. o RF circuit design
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profile PhD (awarded within the last 5 years) of high quality, ideally in machine learning (in the broad sense), complemented by a strong mathematical foundation in probability and/or statistics Research
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fellowship is to contribute to the introduction of new hybrid methods, in the sense that they bridge the gap between "classical" methods (energy minimization, partial differential equations, etc.) and recent