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to machine learning algorithms in order to get uncertainty estimates for parameters governing the distribution of the observed data. The predictive Bayes scheme for uncertainty quantification contains a wide
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. The successful candidate will be joining the Ultracold Quantum Gases group led by Prof. Dr. Leticia Tarruell. The interplay of interactions and gauge fields is responsible for some of the most intriguing phenomena
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drought resilience and adaptation. Current groundwater flow models, however, often exhibit important uncertainties related to input parameters and boundary conditions. Reducing this uncertainty is difficult
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. Possible Activities: The selected candidates will work on Develop novel estimation frameworks for inferring latent risk, ambiguity, and proficiency parameters of other agents in cooperative multi-agent
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 8 days ago
solving complex inverse problems that link measurements to their underlying causes. This PhD interdisciplinary programme focuses on Bayesian methods for estimating physical parameters from high-dimensional
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, such as the ability to estimate certain parameters that are difficult to estimate on separate data sets and improve their accuracy, but require special precautions to avoid unrealistic results. The ultimate
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. This PhD project focuses on improving how we estimate key parameters in land-surface and ecosystem models, which are essential for understanding climate change impacts. The work involves reviewing existing
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PhD Studentship in: Algae speciation and bloom risks in drinking water reservoirs: linking microbiological and environmental parameters to prevent treatment impacts School of Mechanical, Aerospace
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attending an academic Bachelor’s degree in the scientific field mentioned above. Knowledge or experience (preferred) on machine learning or computer vision techniques, and interest in developing such skills
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 11 days ago
improve estimation of rates of snow accumulation, snowmelt, ice melt, and sublimation from snow and ice worldwide at scales driven by topographic variability. We seek projects focusing on the use of machine