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Mobility (IAM), considering ecological, economic, technological, and sociological factors. The RTG's structured PhD program aims to train young researchers in highly automated, networked mobility, featuring
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, and environmental impact Development of dynamic process models for electrified methanol processes under fluctuating power supply from renewable sources Simulation and optimization of the operating
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Mobility (IAM), considering ecological, economic, technological, and sociological factors. The RTG's structured PhD program aims to train young researchers in highly automated, networked mobility, featuring
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, manufacturing and optimizing gene vectors Characterization of vector transduction in vitro and in vivo Radiolabeling of gene vectors for PET/CT imaging Animal studies in collaboration with other researchers and
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PhD Position – High-Temperature Electrolysis – from stack design to operational optimizationFull PhD
this with expertise in high‑performance computing and artificial intelligence using unique scientific infrastructures. At the Institute of Energy Technologies – Fundamental Electrochemistry (IET‑1), we
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Mobility (IAM), considering ecological, economic, technological, and sociological factors. The RTG's structured PhD program aims to train young researchers in highly automated, networked mobility, featuring
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, optimization and modelling tools; Computational Fluid Dynamics (CFD)), Product and Processes Engineering (Space Engineering), Condensed Matter Physics (Fluid mechanics and dynamics) and Applied Physics
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interest in agentic AI, online learning and optimization, and applications in economics. The full-time positions (100%) are initially offered for two years, with the possibility of extension, depending
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changes), Computer Science and Informatics (Numerical Analysis; simulation, optimization and modelling tools; Computational Fluid Dynamics (CFD)), Product and Processes Engineering (Space Engineering
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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