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publications (45%); - Experience in CFD simulation and finite element software for the analysis of building components; energy and thermal simulation; knowledge of digital technologies for geometric definition
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, optimization and modelling tools; Computational Fluid Dynamics (CFD)), Product and Processes Engineering (Space Engineering), Condensed Matter Physics (Fluid mechanics and dynamics) and Applied Physics
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of next-generation lightweight electric vehicles. The work will focus mainly on the development of numerical models (CFD) for the analysis and understanding of the behavior of the solution to be developed
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applications. To achieve this, you will employ computational fluid dynamics (CFD) and machine learning (ML) to investigate degradation mechanisms under various operating conditions and develop strategies
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performance in fuel cell (biogas) and co-electrolysis applications. To achieve this, you will employ computational fluid dynamics (CFD) and machine learning (ML) to investigate degradation mechanisms under
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, optimization and modelling tools; Computational Fluid Dynamics (CFD)), Product and Processes Engineering (Space Engineering), Condensed Matter Physics (Fluid mechanics and dynamics) and Applied Physics
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proficient programming skills. Essential experience includes developing Discrete Element Models (DEM) or hybrid models (e.g., DEM-CFD, DEM-SPH). A proven research record through publications and code
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of Mechanical Engineering). This environment facilitates the exchange of research knowledge with colleagues also working in CFD and ML, both in applied and fundamental areas. The candidate will develop
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aerodynamic methods and tools of turbomachinery design is therefore required, which in turn includes design and optimization in 1D, 2D, 2D Blade-to-Blade as well as 3D computational fluid dynamics (CFD) methods
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contactors. CFD simulation of the modules. 6. Legislation and regulations: Research Fellow Statute, as amended by Decree-Law No. 123/2019, of August 28th; Scientific Research Grant Regulation of the University