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Field
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sites will not be located directly at the source of emissions, which will require transport infrastructure. As part of this work, you will model spatially resolved transformation paths for the energy
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analysis problems, especially tracking the motion of objects, which are driven by real applications in life science research Developing solutions to integrate large foundation models into microscopy image
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civil/electrical/control engineering or mathematics or related study programs with a solid basis in choice modelling and/or reinforcement learning, with knowledge of MATSim is advantageous. Description
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: Prof. Dr. Steven Travis Waller, Chair of Transport modeling and simulation, and co-supervised by at least one additional professor, plus an international tutor of the CRC Requirements: excellent
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mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) High
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combining experiments with computational analysis. Interest developing new methods and analysis tools for emerging model systems. What we offer A cutting-edge research environment Pleasant working atmosphere
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on mesoscale fluid dynamic simulations, microclimatic and turbulence modelling procedures in urban environments shall be performed. Subsequently weather-and turbulence-related limit values shall be formulated
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academic qualification (usually PhD). Job ID:RTG2947-T7 Title:Microclimatic effects: Weather-robust UAS flight planning and operation Investigators:Dr.-Ing. habil. Judith Rosenow, Chair of Air Transport
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experience growing, managing, and phenotyping plants in the field and greenhouse. You have experience using modern approaches in root phenotyping, image analysis, or simulation modeling to understand
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innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry tools