22 experimental-fluid-mechanics Postdoctoral positions at Technical University of Munich
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methods (LBM). For fluid simulations, we utilize the high-performance LBM framework waLBerla, predominantly written in C++, but increasingly adapted for GPU computations through automatic code generation
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to serious and costly accidents due to human error. Solutions to these problems, such as sustainable drives and autonomous navigation, are not yet fully developed and are still at the experimental stage
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will be strongly encouraged to join ongoing local, national and international collaborations with leading theoretical and experimental researchers and contribute to shaping new research directions
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; knowledge in numerical methods and simulation, particularly for partial differential equations, and basic knowledge in mathematical modeling with/and PDEs, with a focus on fluid or biomechanics, porous media
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objective of the research group ‘Crop Physiology’ is to understand the physiology of plants down to the structure and function of genes and proteins as well as relevant mechanisms, which allow optimizing
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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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modeling and prediction Integration of perception, planning, and control for robust real-time robotic performance Requirements PhD Position: Master’s degree in Robotics, Mechanical Engineering, Electrical
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) • Experience working in a wet lab environment. • Fluency in oral and written English • Interest in working in a multidisciplinary and international team • Experience with experimental techniques including
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. The aim of our group is to improve the understanding of the trade-offs between production, mitigation and conservation in livestock-based systems, and to identify innovative mechanisms for landscape-level
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the understanding of the trade-offs between production, mitigation and conservation in livestock-based systems, and to identify innovative mechanisms for landscape-level management. Our group combines empirical work