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into machines that enable the intricate genomic immune system that is described briefly above. At the same time, by understanding how ‘basic’ machinery can be re-purposed we also learn new things about that
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combines state-of-the-art computational multiscale modelling (using DFT/TDDFT methods, collision theory, molecular dynamics, stochastic dynamics, Monte Carlo and analytical methods) and its thorough
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lifetimes for model development Use an inline endoscope and an optical fiber Doppler probe (OFDP) to determine bubble surface loading as well as bubble size and velocity Integrate and interpret measurement
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institution. At the Faculty of Computer Science, Institute of Artificial Intelligence, the Chair of Machine Learning for Computer Vision offers two full-time positions as Research Associate / PhD Student (m/f/x
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this with expertise in high-performance computing and artificial intelligence using unique scientific infrastructures. Are you excited about working at the interface of natural and computer sciences? At
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biological techniques, as well as animal models, will be applied. We offer: Embedding in an internationally competitive scientific environment An established, broad spectrum of scientific methods A wide range
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coating, iii) investigation of system design from small-scale to potentially pilot scale, and iv) application to micropollutant removal. Modelling aspects are open to exploration at molecular and process
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of the German Armed Forces Munich), the DLR (German Aerospace Center) with its Oberpfaffenhofen institutes, and the BHL, the Bauhaus Luftfahrt. This pooling of research, graduate programmes and teaching merges
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months three transnational secondments of two months each are planned to acquire further knowledge and foster scientific exchange. Your tasks Design and construction of a physical model of the
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: System-Level Impact Analysis of IAM using Agent-Based Models Supervisor: Prof. Dr. Regine Gerike, Chair of Mobility System Planning and co-supervised by at least one additional professor