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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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aneurysms. Arterial geometries are derived from medical scans (e.g., CT) of real patients, which are suitably meshed and processed for numerical treatment using Lattice-Boltzmann methods (LBM). For fluid
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 2 months ago
Job Code: MPIDS-W083 Job Offer from February 26, 2025 For the independent research group “Theory of Biological Fluids” headed by Dr. David Zwicker we seek to fill a Postdoctoral Position (m/f/d) in
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27 Feb 2025 Job Information Organisation/Company Max Planck Institute for Dynamics and Self-Organization Research Field Physics Researcher Profile Recognised Researcher (R2) Country Germany
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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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are derived from medical scans (e.g., CT) of real patients, which are suitably meshed and processed for numerical treatment using Lattice-Boltzmann methods (LBM). For fluid simulations, we utilize the high
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experimental approaches Experience in several of the following fields: aerosol physics and fluid dynamics, electron or x-ray imaging, bio-sample handling, biophysics, vacuum operation, cryogenics, laser physics
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operation of novel experimental approaches Experience in several of the following fields: aerosol physics and fluid dynamics, electron or x-ray imaging, bio-sample handling, biophysics, vacuum operation
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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