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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
The Mathematics and Computer Science (MCS) Division at Argonne National Laboratory invites outstanding candidates to apply for a postdoctoral position in the area of uncertainty quantification and
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control (MPC) under uncertainty for autonomous systems. The research aims to develop state-of-the-art numerical methods for solving challenging belief-space optimal motion planning problems and their
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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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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 9 hours ago
. Description: Uncertainty quantification is a field with wide applicability to the design, development, and science return of space science missions. There is growing interest for the tools and practices
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research profile in inverse problems and computational mathematics. About the job This project focuses on developing advanced methods for uncertainty quantification in inverse problems, i.e., mathematical
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: Cuantificación de Incertidumbre Bayesiana (Bayesian Uncertainty Quantification, BUQ) Appl Deadline: 2025/10/30 11:59PM * (posted 2025/09/08, listed until 2025/10/30) Position Description: Apply Position
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Postdoctoral Researcher to support a project studying the Center’s research theme, Uncertainty. If you have experience and wish to explore how to build systems (both foundational or applied) that can handle
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, Uncertainty. If you have experience and wish to explore how to build systems (both foundational or applied) that can handle uncertain or incomplete data prevalent in urban decision-making scenarios, please
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, and uncertainty-aware algorithms for autonomous driving systems. The position focuses on developing robust decision-making, planning, and control methods that address uncertainty arising from perception
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 10 hours ago
development skills; and experience and deep understanding of the needs for interpretive transport validation exercises, such as profile fitting, interpretive power balance, uncertainty quantification, inversion