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Field
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quantitative properties of an object or medium from measurements of waves that have propagated through it. Mathematically, such problems lead to large-scale nonlinear inverse problems governed by partial
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, such as statistical learning, causal inference, experimental design, probability, stochastic PDEs, algebraic statistics, normalizing flows, scientific machine learning, optimization, inverse problems
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Summary Seeking one motivated MS engineering student to support a research project on real-time refractory thickness measurement using thermal sensing, inverse heat-conduction model, and 3D
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, high-performance scientific computing, tensor methods, and scalable algorithms. Optimization: continuous and discrete optimization, computational optimization, inverse problems, and optimization methods
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Position Information Posting Number F00797P Position Title Assistant Professor in Mathematics - Inverse Problems & Imaging Department Mathematics Location Arlington Job Family Faculty Position
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 6 days ago
research opportunity invites a participant to investigate that coupling in both directions in support of NASA's microwave remote sensing missions. In the forward direction, physically based inversion of soil
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for entry into a PhD program. A background in machine learning, inverse problems, scientific computing, or related data-driven methods is highly desirable. You are curious about combining physical modeling
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intellectually stimulating environment to enable high quality work in strategic directions that are of significant impact to industry, science and technology. For more details, please view https://www.ntu.edu.sg
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Website https://www.academictransfer.com/en/jobs/363422/postdoc-in-monitoring-of-therma… Requirements Additional Information Website for additional job details https://www.academictransfer.com/363422/ Work
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for automated interpretation. Inferring user activity directly from aggregate or sub-metered power consumption is a challenging inverse problem: activity signatures are noisy, non-stationary, and often ambiguous