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Your Job: The electrocatalytic interface engineering department led by Prof. Dr.-Ing. Simon Thiele focuses on synthesis, manufacturing, analysis and simulation of functional materials to find
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to the FAIR-ification of data, establishing systematic data collection and metadata extraction protocols to enhance machine learning-based software applications for materials science. Your Profile: Master’s
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addition to technical models allowing to assess technical scaling and an optimal operation. The optimal plant design is identified by considering the energy supply system, the choice of capture technology, the DAC
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for self-supervised learning in science Engage in national and international ML/DL communities, most importantly the Helmholtz Foundation Model Initiative Present research results at scientific meeting
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preparation Deriving insights for film and device fabrication based on the above described workflow Your Profile: Masters degree in physics, materials science, physical chemistry, electrical engineering and
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the field of energy engineering, optimization, climate change, and climate change adaptation. Software development, particularly in Python will constitute a significant portion of your work. Upon completion
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in physics, physical chemistry, chemical engineering, or related field Knowledge and competences in physical theory and modelling Experience and interest in computer programming Basic knowledge
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, chemistry, material science, chemical engineering or related disciplines Experience in the field of energy storage Knowledge of X-ray methods Experience with programming languages (ideally Python) Fluent in
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of quantum physics and interest in quantum technology Strong mathematical education, in particular, in relation to linear algebra Strong programming experience Ability to effectively communicate in written and
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engineering, computer engineering, computer science, or related fields Background in device physics and analog or mixed-signal circuit designs Strong skill in mixed-signal circuit designs (active filter