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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 11 days ago
employs about 300 people. We are part of the Göttingen Campus, a collaboration between the university and non-university research institutions. The Laboratory for Fluid Physics, Pattern Formation and
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 8 days ago
Job Code: MPIDS-W086 Job Offer from June 23, 2025 We seek to fill one position in the research group on Turbulence and Particles in Fluids lead by Dr. Gholamhossein Bagheri and in collaboration with
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) and donor material from healthy individuals and multiple sclerosis patients (blood and cerebrospinal fluid/CSF), combined with T and B cell receptor sequencing from patients and healthy donors. The aim
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coupled with DESI Imaging Mass Spectrometry, HPLC-DAD-MS, HPLC-HRMS, GC-MS, automated extraction systems such as Accelerated Solvent Extraction (ASE) and Supercritical Fluid Extraction (SFE), FT-IR
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of fluid dynamic modeling and the analysis of thermomechanical stresses, you will accompany the entire development process – from the optimization of electrochemical performance to the elaboration
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; knowledge in numerical methods and simulation, particularly for partial differential equations, and basic knowledge in mathematical modeling with/and PDEs, with a focus on fluid or biomechanics, porous media
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methods (LBM). For fluid simulations, we utilize the high-performance LBM framework waLBerla, predominantly written in C++, but increasingly adapted for GPU computations through automatic code generation
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. The role involves setting up experimental models using Particle Image Velocimetry (PIV) and performing Computational Fluid Dynamics (CFD) simulations to analyze fluid flow and deposition patterns. The data
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and simulation aspects across a wide range of fields - from biomechanics and geophysics to polymer-fluid coupling. Further areas of interest include numerical algorithms for high-dimensional problems
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investigate methods that eventually will automate crucial design steps. In addition, we are developing simulators (on various abstraction levels; using, e.g., Computational Fluid Dynamics) which enables us to