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Field
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is to investigate the optimal configuration for utility-scale AWE farms, considering the physics, economics, and environmental impact. To determine the optimal scaling strategies for kite farms, a
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possess strong programming skills in Python and C++, with experience in PyTorch and pybind11 for developing and optimizing deep learning models. Familiarity with Sentinel-2 satellite imagery and experience
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, differential equations, geometry/topology, numerical analysis, optimization, and statistics. Part of the research is also carried out in close cooperation with other fields of science and technology at NTNU, as
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PhD student to establish recipes to provide post-plasma catalysis with different C2Hy distributions and different enthalpy content for optimization of post-plasma catalysis into C2H4. PhD candidate in
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windows as well as to optimize the tooling geometry. These process simulations require efficient numerical algorithms to be practical and to enable robust optimization. Therefore, in this project you will
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particular, we will use topology and shape optimisation methods to compute the optimal domain shapes that can stabilise solutions with desired/prescribed properties. We will use methods from inverse problems
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, including 4 training schools and two workshops. As a participant of the project, the PhD student will become part of a team at DTU with numerical and experimental expertise in photonic computing
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 27 days ago
finalization of the foundations of dual-tracer imaging using a GATE-based Monte Carlo simulation # Implementation of the developed algorithms within our modular, C++-based and cluster optimized PET image
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layers. 1-Context Turbulent flows dictate the performance characteristics of numerous industrial equipment and environmental applications. One important consequence of turbulence is to increase the mixing
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impact of energy generation. This PhD project is part of the MSCA Doctoral Network AWETRAIN (Airborne Wind Energy TRAining for Industrialization Network). Its objective is to investigate the optimal