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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 23 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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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 26 days ago
Understanding the individual and relative motion of particles is fundamental to understanding transport processes in complex flows. Large-scale transport in atmospheric flows is well understood and measured by
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04.06.2025 Application deadline: 30.06.2025 The Theoretical Particle Physics Group at the Institute for Theoretical Physics at Tübingen University invites applications for the position of a
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Area of research: Scientific / postdoctoral posts Starting date: 01.07.2025 Job description: GSI Helmholtzzentrum für Schwerionenforschung in Darmstadt operates one of the leading particle
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of nanoparticle formulations for heating in alternating magnetic fields. Create a magnetic heating setup to assess the performance of your materials. Integrate particles into composite materials for remote
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QCD, phenomenology of XYZ, higher order perturbative calculations inside effective field theories. The particle and nuclear theory group at the TUM School of Natural science is lead by Prof. N
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role in the global carbon cycle by transferring carbon from the surface ocean to the deep sea through the formation, sinking, and remineralization of organic particles. Despite its importance, our
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-deep knowledge in the applications of Hyperspectral Imaging, Biospeckle Imaging, Laser-Light Backscattering Imaging, LEDs, and Bandpass Filter-Based Imaging techniques Basic knowledge of substrate
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and function of matter, from the smallest particles of the universe to the building blocks of life. In this way, DESY contributes to solving the major questions and urgent challenges facing science
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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