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impeller performance, analyze hydrodynamic characteristics, and identify key synthesis parameters influencing material quality. The resulting models will act as a predictive tool for process optimization and
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or reconstruct the missing links. The first step is to explore different optimization methods using low rank tensor minimization and tensor decompositions paired with auxiliary information in order to recover
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for fluid dynamics, mixing, and reaction kinetics in the CSTR. Implement advanced numerical schemes and perform high-resolution CFD simulations of two-phase flow. Optimize impeller geometry and reactor design
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mining waste deposits (MATs). This project integrates mineralogical and mechanical characterization, pilot-scale testing, and advanced process simulation, with the objective of optimizing grinding
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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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multiplex and multilayer networks alongside with the observed links in order to predict or reconstruct the missing links. The first step is to explore different optimization methods using low rank tensor
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advancements and practical implementations optimized for modern HPC systems. The postdoc will primarily contribute to one or more of the following research areas: Development of efficient numerical linear
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testing, and advanced process simulation, with the objective of optimizing grinding performance and enhancing resource recovery. The ideal candidate will have a strong background in mineral processing