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Field
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quantum computers, which represent a promising path towards fault tolerant and scalable quantum computing. The project addresses a broad range of optimization problems relevant to both science and industry
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(Numerical Analysis and Applied Mathematics) develops numerical algorithms and software for large-scale problems in science and engineering. Its research ranges from algorithm design and analysis to software
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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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, manufactured using a hybrid PIP (Polymer Impregnation & Pyrolysis) - CVI (Chemical Vapor Deposition) process from a ceramic fiber preform. This process requires optimization, whereby the structure of the porous
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. The researcher will also design data-driven numerical approaches to address a variety of real-life optimization models including disaster and emergency logistics, supply chain and transportation. Specific
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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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industry. Our photonics research lab has set modern tools for the design, testing, and optimization of photonic circuits. It is open for collaboration with researchers with a background in basic research
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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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areas will be considered when selecting candidates: Machine Learning, Neural Networks, Numerical solutions of Partial Differential Equations and Stochastic Differential Equations, Numerical Optimization
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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