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Max Planck Institute for the Structure and Dynamics of Matter, Hamburg | Hamburg, Hamburg | Germany | about 1 hour ago
develop state-of-the-art theoretical and computational methods to model strong light–matter coupling in and out of equilibrium, across gaseous, liquid, and solid-state systems. Key responsibilities The PhD
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-renowned universities in its fields. The University is engaged in economic and human development and puts research and innovation at the forefront of African development. A mechanism that enables it to
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candidate will play a key role in developing and advancing new models and simulations for Computational Fluid Dynamics (CFD) hypersonic codes. Specific tasks include developing new turbulence and transition
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, including electrically conductive membranes. The successful candidate will work under the supervision of Professor Raed Hashaikeh in the Mechanical Engineering Department, collaborating with a
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Apply now Job no:535477 Work type:Faculty - Pro Tempore Location:Eugene, OR Categories:Research/Scientific/Grants, Earth Science Department: CAS Earth Sciences Rank: Research Assistant (Type B
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have a PhD in environmental engineering, earth or environmental engineering, or related fields, with a background in ecohydrology. Experience in ecohydrological modeling and remote sensing is desired
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application! Work assignments As a postdoctoral fellow, your main task will be to conduct cutting edge computational social science research. The research will be carried out within the context of the Swedish
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new smart materials, at the intersection of materials science, chemistry, and engineering. A strong background in thermal or mechanical characterization of surface and bulk properties of solids from
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: Statistical signal/image processing, deep learning, machine learning, neuromorphic computing Good communication skills and an appropriate publication record are essential. Solid knowledge of Python and C++ is
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doctoral studies / focus on solid state physics or chemical physics Professional skills: Development of ab initio methods Methodological skills: Python, Fortran, C, C++ High performance computing Good