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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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H2 profiles in collaboration with our modeling department Your Profile: MSc in meteorology, physics, chemistry, environmental sciences or a related field with good final grade (German system equivalent
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Your Job: You will strengthen the data science and machine learning activities of the IAS-9 with exciting new topics. You will work in a multidisciplinary team of enthusiastic data scientists
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for an enthusiastic researcher who is quick to grasp new concepts and ideas and can solve complex problems with high-quality software solutions. You will work with machine learning, HPC, and domain science experts and
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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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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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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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Your Job: Analysis and integration of diverse biological data from the field of plant sciences (large scale genomic, transcriptomic, proteomic, metabolomic and/or single cell data) using cutting
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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