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/Qualifications Strong knowledge of mathematical modeling and numerical methods Experience in computational fluid dynamics and pipeline transport modeling Proficiency in programming and scientific computing (e.g
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. • Mechatronic systems. • Artificial intelligence methods. • Control theory and basic organisational activities for the benefit of the Department, the Faculty and the University. Where to apply E-mail
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machine components. • Application of modern measurement methods, including 3D scanning, for geometry inventory, deformation analysis, numerical model validation, and diagnostics of machine components
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sensitive sensing, NCN OPUS 24 No. 2022/47/B/ST5/02337 Leader Dr Maciej Cieplak Selective and sensitive chemosensing is crucial for numerous aspects of modern civilization and technology. Within this Project
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strongly correlated quantum systems. Experience (supported by peer-reviewed publications) with models and analytical or numerical methods/theories such as quantum mechanics, solid state physics, lattice
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measurements with numerical simulations (e.g., FEM-based workflows) • Hands-on experience with data preprocessing, feature engineering, and model validation in engineering contexts • Familiarity with Digital
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studies with a very good or excellent final degree and a master's thesis in condensed matter theory or a closely related discipline. Experience with models and analytical or numerical methods/theories
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national and international research projects, development of competences in modern design methods, numerical calculations, and the implementation of research and development work, as well as improvement
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experimental data with numerical models. Ability to use specialised software and computational tools supporting CFD modelling, as well as basic knowledge of model verification and validation methods using
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. Collaboration in developing methods for integrating histological data with molecular research results. Where to apply E-mail marcin.poreba@pwr.edu.pl Requirements Research FieldChemistry » OtherEducation LevelPhD