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dissemination in the field of contemporary history with a particular focus on digital methods and tools. The C²DH's ambition is to venture off the beaten track and find new ways of doing, teaching and presenting
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to numerical methods for kinetic equations. Mathematical topics of interest include high-dimensional approximation, closure models, machine learning models, hybrid methods, structure preserving methods, and
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uncooperative spacecraft . Develop novel methods for characterization and quantification of input-output bounds in an AI-augmented perception system: Develop novel methodologies and tools for characterizing and
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, United States of America [map ] Subject Area: Numerical Methods for Nonlinear PDEs Appl Deadline: (posted 2025/08/27, listed until 2026/02/27) Position Description: Apply Position Description The Mathematics Department
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the development and coupling of numerical methods for solid mechanics modeling Experience in digital rock technology, including advanced imaging and related analysis Experience in the performance of high pressure
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elements methods Modern machine learning software tools and frameworks Implementation of scalable numerical algorithms on HPC architectures Excellent written and verbal communication and interpersonal skills
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have a strong interest in both theory and numerical work. Numerical work involves code development (e.g., changing the C++ LAMMPS code, programming of data analysis tools, etc.), carrying out large-scale
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is currently seeking a Postdoctoral Research Associate in the development and application of hybrid numerical-asymptotic methods to nonlinear systems. Your key responsibilities will be to: work on an
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early-career researcher in applied mathematics, physics, or engineering, with expertise in fluid mechanics1, non-Newtonian fluids, numerical methods, and scientific computing2. Background or strong
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the Future: Be part of building a cutting-edge research institute from the ground up! Postdoctoral Positions available in … https://www.oeaw.ac.at/aithyra/postdoc-search Designing New High-Throughput Methods