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Your Job: To further develop the high-temperature electrolysis and fuel cell technology (Solid Oxide Cell, SOC), you will take over management of the merged departments "Electrochemistry" and
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engineering department led by Prof. Dr.-Ing. Simon Thiele focuses on synthesis, manufacturing, analysis and simulation of functional materials to find an optimum structure on small scales from the micrometer
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engineering, materials science, mechanical engineering or other related fields Strong background in physical chemistry and thermodynamics including the development and understanding of phase diagrams Experience
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of scientific publications and project reports Your Profile: A very good university degree (Master or diploma) in materials engineering, materials science, mechanical engineering or other related fields Strong
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plant design is identified by considering the energy supply system, the choice of capture technology, the DAC-plant’s technical design, the DAC-plant’s operational concept and the positioning of the DAC
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/electronic engineering, computer science, computer engineering, physics, and related fields. For IC projects a strong electronics background, with experience in design and simulation of analog, digital
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. Additionally, enjoyment of teamwork is an important requirement. Masters degree in electrical/electronic engineering, computer science, computer engineering, physics, and related fields. For IC projects a strong
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activities, semantic and infrastructural engineering in the field of Material Science, e.g. within NFDI-MatWerk Dissemination of developed tools and concepts within interest groups, workshops and training
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and Stuttgart University. Your Profile: You are an enthusiastic and motivated researcher You have a Masters degree and a PhD in physics, chemistry, engineering or related fields Ideally you also have
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Internship / Master Thesis – Quantum Optimal Control Algorithms for Electrochemical NMR Applications
the theoretical and computational infrastructure to employ quantum optimal control methods, where simulated spin models are directly used to engineer NMR experiments. At the core of this project stands the Python