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Field
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methods for analyzing complex experimental or imaging data. Demonstrated expertise in several of the following areas: inverse problems, statistics, optimization, uncertainty quantification, and/or computer
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been proposed: traditional computer‑algebra methods [3], reduction of the problem modulo a prime p [6, 2], and symbolic‑numeric methods [4, 1]. This postdoc proposal concerns the second modular approach
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). Experience in the application and development of computational methods/tools or machine learning algorithms. Good computer programming skills in R/Matlab/PerlPython. Knowledge of basic molecular biology
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Division (MSTD) at Oak Ridge National Laboratory (ORNL), and who will focus on ORNL's continued development of methods to quantify shear (yield) strength of monolithic ceramic materials as a function of
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areas : 1/ Development of methods to estimate residential environmental exposures • Develop spatialized indicators of exposure to atmospheric contaminants (gaseous pollutants and pesticides) based
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, optimization, and characterization integrating imaging, experimental metadata, and diffraction outcomes. Design and deploy computer vision methods to detect and track crystal growth. Develop closed-loop
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understanding of the interrelations between air quality, climate change, and human health, with expertise in atmospheric composition modeling, air quality forecasting, satellite-based PM2.5 estimation, and
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physics-informed and physics-ML hybrid approaches that integrate domain knowledge with data-driven methods to advance hydrological process understanding and prediction. Conduct multimodal, multiscale data
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License/Registration/Certification n/a Physical Requirements Some standing or walking. Sitting at computer workstation for extended periods. Repetitive motion. Lifting, pushing, or pulling of objects up
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
this context, the offer is about continual audiovisual robot perception, and aims to develop methods and algorithms to continuously extract cues about human behaviour from audio and visual data in real-world