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, applied mathematics, or a closely related field Strong background in fluid mechanics, heat transfer, and numerical methods Practical experience in CFD; experience with OpenFOAM is considered a strong
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method based on large-scale and laboratory-scale experiments supported by numerical modelling to: Better understand the fire behaviour of the new façade system, to propose fire safe constructions and to
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regimes. This PhD project aims to develop predictive pore network models integrated with thermodynamics and upscaling methods toward reservoir-scale applications. We seek candidates with a strong background
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and microstructure-based modeling Experience with numerical methods for PDEs Programming skills in Python (knowledge of C++, Fortran or HPC is a plus) Scientific curiosity and critical thinking Ability
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the enhancement of the efficiency or figure of merit of the stacks. Moreover, (ii) by using and combining various experimental techniques and methods available at the laboratory (harmonic Hall, spin pumping, FMR
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shaping will be central to the study. The numerical model will be based on the boundary element method (BEM) and semi-analytical approaches developed at I2M. The experimental proof-of-concept will leverage
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Computational and Theoretical Condensed Matter Physics in the Department of Physics (Ref.: 534748). Applicants should possess a Ph.D. degree in Condensed Matter Physics. Experience in numerical techniques and
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member of "Carb2Mol" and considered for integration into the Graduate School “Engineering Covalent Bonds in Molecules and Materials” Ec=m2 (RTG 3082; https://www.uni-saarland.de/forschen/ecm2.html
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finding techniques, such as Newton's method, after adapted numerical discretization. There is a challenge in extending existing BVP schemes to reaction-diffusion problems, choosing suitable spatial and
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uniformity, dynamic response, and integration compatibility with modern microelectronic and photonic platforms. The project will combine numerical modelling, optimisation methodologies, and experimental