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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 5 hours ago
reduction and manifold learning * High-dimensional inference and feature selection * Generative modeling and digital twins * Reliability and interpretability of ML methods The postdoctoral researcher will be
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and determination? We are currently seeking a/an University Assistant postdoctoral 56 Faculty of Mathematics Startdate: 01.05.2026 | Working hours: 40 | Collective bargaining agreement: §48 VwGr. B1 lit
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, Mathematics, or closely related fields. • Experience conducting experimental, theoretical, or computational research. • Familiarity with mathematical modeling, data analysis techniques, or computational tools
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] Subject Areas: Applied Mathematics, Computational Research Appl Deadline: (posted 2026/02/24 05:00 AM UnitedKingdomTime, listed until 2026/08/25 04:59 AM UnitedKingdomTime) Position Description: Apply
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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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2 Mar 2026 Job Information Organisation/Company Met Éireann Department Research & Applications Division Research Field Computer science » Modelling tools Mathematics » Computational mathematics
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postdoc to join our team at the Division of Applied Mathematics and Statistics, Department of Mathematical Sciences, and contribute to research on stochastic and statistical models for large-scale shape
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and numerical algorithms for modeling and simulation of nuclear systems. Computational Nuclear Engineers within the RTHPCM group will work with group, section, and division members and external
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) simulations and reduced order modeling of turbulent and reacting flows relevant to advanced propulsion and power generation systems, such as gas turbines and detonation engines. The successful candidate’s
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. These applications include, but are not limited to, anomaly detection, modulation classification, sensing, and adaptive spectrum optimization in diverse operational environments. Your work will focus on modeling and