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for the efficient formation of high-value compounds. Advanced NMR methods and computational data analysis will be compounded to devise novel reactions towards pharmaceutical precursors, polymer building blocks and
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process. An integral part of the project will be the development of enhanced data-driven physics methods to achieve reliable prediction of material removal rate and material removal distribution
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topic of this project and who have academic training in one or more of the following areas: A master’s degree in chemistry, chemical engineering, materials science, physics, or a related discipline
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-essential components of the problem, thereby reducing the size of the subproblems and accelerating the overall solution process. The second line targets the convergence issues often encountered in column
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process. An integral part of the project will be the development of enhanced data-driven physics methods to achieve reliable prediction of material removal rate and material removal distribution
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spatial planning. Translate scientific results, in collaboration with stakeholders, into clear, engaging visualizations and communication materials that support understanding and inform evidence-based
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level equivalent to a two-year master's degree. The ideal candidate will have a background in photonics and condensed-matter physics. You should have a passion for theoretical and computational physics, a
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samples, by the development of advanced computational multiphysics models of stress corrosion cracking and coupling these with process-microstructure models (being developed within MicroAM project). Main