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project. This research position will investigate models and their uncertainty for underwater acoustic propagation to better estimate the spatial and temporal properties of underwater soundscapes
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Postdoctoral Research Assistant in Decision-making under uncertainty for robots Grade 7 : £39,424 - £47,779 per annum We are looking for a post-doctoral research assistant to join the GOALS group
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the quantification and representation of uncertainty within and between these models. Addressing these questions is essential if their predictions are to be used for scientific understanding and societal decision
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The University of Amsterdam invites applications for a postdoctoral researcher position focused on evaluating nascent sustainable technologies amidst high uncertainty. We are looking for a talented
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tasks require high-frequency evaluations of forward models, in order to quantify the uncertainties of rock and fluid properties in the subsurface formations. Therefore, the objectives of this research
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statistical and machine learning, deep learning, chemometrics, multimodal data fusion, computer vision, uncertainty-aware modeling, stochastic control, optimization, and deployable edge-to-cloud decision
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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | 13 days ago
-sensitive modeling, high-fidelity experimental characterization, and uncertainty quantification capabilities for metallic aerospace materials, with emphasis on additively manufactured (AM) metals
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 13 days ago
and its spatial variability; use of precipitation coherence as a validation and uncertainty-quantification pathway for high-resolution soil moisture from NISAR and future L-band missions (e.g., ROSE-L
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models can support energy-system modelling and optimization, including applications such as prediction, surrogate modelling, uncertainty quantification, and decision support. Coordinate the joint research
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machine learning for the next generation of AI models – uncertainty-aware foundation models, generative models and world models – with the support of competent and friendly colleagues in an international