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the adoption and digital transformation in the renewable energy sector. This initiative seeks to harness the latest advancements in cloud computing solutions, data analytics, artificial intelligence, and
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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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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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data extraction and machine learning models An analytical thinker with proven problem-solving abilities and a commitment to pushing the boundaries of interdisciplinary collaboration Experience in
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, particularly in Python, Django, or similar frameworks, with a robust understanding of data extraction and machine learning models. An analytical thinker with proven problem-solving abilities and a commitment to
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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. Place of employment: Jülich
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Your Job: You will oversee the focus area "Information" and support corporate development department as well as the board of directors in questions concerning the strategic alignment of the area and
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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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description Higher level alignment of semantic descriptions, intra- and inter- domain harmonization of metadata, e.g. through integration of resources in central information systems General exchange with
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important as high accuracy Supervise student projects at BSc, MSc, and PhD level Work with experts at the Jülich Supercomputing Centre (JSC) to run your algorithms/tools on large distributed computer systems