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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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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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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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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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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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Your Job: One essential step towards the ramp-up is the identification of site-specific optimal design of DACS plants, which will be the focus of the advertised PhD. To identify optimal DACS plant
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salary. Further information on doctoral degrees at Forschungszentrum Jülich (including its various branch offices) is available at https://www.fz-juelich.de/en/careers/phd We welcome applications from
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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