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Field
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: “Optimizing microwave plasma-based reduction of metal oxides” under the supervision of Prof. von Keudell, Chair for Experimental Physics – Reactive Plasmas at the Faculty of Physics and Astronomy, Ruhr
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. The techniques used will include Laser Doppler Vibrometry (LDV) and Air Coupled (AC) ultrasound detection. The candidate will design optimized setups for (i) vibration excitation by an impactor or ultrasonic
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, engineers, and technicians. Prototyping, testing, and optimizing the fibre systems to meet the stringent requirements and standards for astronomical instrumentation. Document development processes, analyse
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laboratory and pilot plant Knowledge of electrolysis technologies (preferably in AEM) and/or pilot-scale engineering A proactive attitude and a strong interest in exploring and optimizing cutting-edge
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science, industrial engineering, or a comparable field (Master’s degree) Knowledge of modeling, optimization, and data analysis of energy systems Interest in electricity markets, energy system analysis, and model-based
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following areas: Strong foundation in machine learning, optimization, and deep learning algorithms, including Transformer architectures. Hands-on experience or solid theoretical knowledge of LLMs/SLMs
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, configuration, and independent operation of these systems Further development and optimization of graphical user interfaces for demonstrators used to visualize measurement results from laboratory setups
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to make them usable for transparent energy system analyses. You will process and semantically enrich the collected data before it is integrated into a knowledge-graph-based metadata platform. In
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to improving human health. Are you eager to put your theoretical knowledge into practice and gain exciting insights into interdisciplinary cutting-edge research? Then you’ve come to the right place! Fraunhofer
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knowledge in discrete mathematics and in one area of mathematical optimization (e.g., discrete optimization, convex optimization) strong interest in basic research using rigorous mathematical methods very