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, Process Engineering, Computational Science, or a related discipline Strong foundation in fluid mechanics, gas–liquid two-phase flows, numerical methods (FVM, FEM), and two-phase flow instrumentation
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core and advanced courses in mathematics (e.g., calculus sequence, linear algebra, differential equations, probability and statistics, numerical methods, optimization, dynamical systems, and modeling
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to sign the contract. More information is available on: https://www.dges.gov.pt/pt/pagina/reconhecimento . Workplan and the objectives to achieve: This work aims to develop a numerical approach based on
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measurement techniques). Desirable additional qualifications include knowledge in additive manufacturing (3D printing) and experience with numerical simulation methods (e.g., finite element methods, FE
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Functional Theory (DFT) Familiarity with artificial intelligence methods Good knowledge of electronic structure methods Experience with Linux, Git and related tools Knowledge in the field of high-performance
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asymptotic analysis and other perturbation methods, and numerical, i.e. an existing in-house code will be modified to achieve the objectives. This project offers the unique opportunity to develop strong skills
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generalizations—combining methods rooted in statistical physics and theoretical computer science. The research work can be more centred on analytical approaches or numerical experiments depending on the profile
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focused on advancing computational methods for synchrotron, free-electron laser (FEL), and related scientific challenges. SciQC combines expertise in mathematics, numerical algorithms, high-performance
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"Phase-space-inspired numerical methods for high-frequency wave scattering: from semiclassical analysis through numerical analysis to implementation". The design of fast and reliable algorithms
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: Applications accepted all year round Details Data assimilation combines physical models with experimental or numerical data to produce dynamically consistent flow reconstructions. In turbulence, where full