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100%, Zurich, fixed-term We are seeking a highly motivated and skilled Postdoctoral Fellow in Microneedle Engineering for Wearable Healthcare Devices to join our dynamic and interdisciplinary
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, Faculty of Science and Technology . The position is connected to the Sea Ice Physics Division of the Alfred Wegener Institute (AWI) and the NOAA Geophysical Fluid Dynamics Laboratory (GFDL). General
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The TUM School of Computation, Information and Technology at the Technical University of Munich (TUM) welcomes applications for a PhD or Postdoc Position (m/f/d, 100%, 2 years+) in Numerical Mathematics
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focuses on building scalable, accreditation-ready analysis workflows to detect and classify microplastics in complex sample types such as drinking water, plant-based beverages, and biological fluids. As a
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industrial and academic partners. The overall goal of the project is to optimize the design of water eletrolyzers for efficient green energy production. You will be conducting Computational Fluid Dynamic (CFD
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Equations, Mathematical Physics, Fluid Dynamics, Mathematical Biology, Mathematical Epidemiology are encouraged to apply. Responsibilities for these positions include mathematical research, undergraduate and
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chemistry. Extensive experience in membrane development, testing and polymer synthesis, functionalization, modification, are mandatory. Knowledge or mastering computational fluid dynamics software and
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positions, and positions for distinguished professorship. Candidates in areas including, but not limited to, Computational Mathematics, Numerical Analysis, Computational Fluid Dynamics, Oceanic and
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the National Center for Atmospheric Research (NCAR) and the National Oceanic, Atmospheric Administration's Geophysical Fluid Dynamics Laboratory (NOAA GFDL), and will foster new collaborations around ML/AI with
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Pohang University of Science and Technology (POSTECH) | Republic, Kansas | United States | 2 months ago
-kinetic systems, quantum-kinetic systems, and mathematical biology from the perspectives of mathematical analysis and machine learning. All researchers working on fluid dynamics, kinetic theory, dispersive