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satisfactory performance and availability of funding. Research topics of interest include numerical methods for scientific machine learning and AI, and their applications to various science and engineering
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phenomena in magnetic solids and molecules exhibiting strong spin–orbit coupling effects. The candidate is expected to have expertise in the development of theoretical or numerical methods for solid-state
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The University of North Carolina at Charlotte | Charlotte, North Carolina | United States | 2 days ago
for : Developing numerical methods and perform high fidelity simulations of hypersonic flow phenomena Minimum Experience / Education: A Postdoctoral Fellow (" Create a Job Match for Similar Jobs Logo About The
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based on empirical studies and/or model simulations. The candidate should assemble and evaluate quantitative proxy reconstructions, and apply geospatial and/or numerical modeling methods to investigate
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Computational Fluid Dynamics. Operational skills : Physical analysis of fluid dynamics, advanced skills in programming and numerical methods, writing scientific reports and articles, presenting at scientific
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at the intersection of numerical linear algebra and advanced HPC. The candidate will join an international environment, with opportunities to collaborate with experts from the USA, and KAUST and publish in top-tier
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polytopal numerical methods The conception of discrete complexes (de Rham and extended complexes) The application to various models of MHD and flows in porous media The numerical analysis of the schemes
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physics, etc. Proficiency in Python or other scientific programming languages. Programming skills in numerical methods for image processing and AI/ML methods for quality improvement are advantageous
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Forest Sector Industry: A Mixed-Methods Approach.” This interdisciplinary research initiative integrates stakeholder engagement, market analysis, and policy evaluation to develop a strategic
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for the project, especially in conjunction with their well studied genetics and recently developed high-throughput single-cell phenotyping methods based on microfluidics. The output will be generalizable to a much