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include: Researching, in particular, publicly available data on current and future materials for energy technologies Implementing the materials in our technology database and in our energy system model
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asset that can help accelerating research on electrochemical systems. The focus on the thesis work is on recovering these data and define what data are needed and how they have to be structured and stored
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order to find transformation scenarios without material gaps. Your tasks in this context include: Researching, in particular, publicly available data on current and future phased-out material flows and
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Construct and operate continuous experimental plants Use state of the art techniques for the characterization and optimization of applied catalysts Develop analytical procedures and data processing methods
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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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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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flexibility Apply advanced data analytical techniques to analyze simulation findings and draw significant insights Determine cost-effective methods for grid reinforcement through performance evaluations Present
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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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, conferences, and as scientific papers Contribute to educational events, such as hackathons, data challenges and courses Your Profile: Excellent Master`s degree in computer science, science, engineering or in a
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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