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of the possible influence of storage-related factors on the LOHC purity Method development and application of suitable analytics (e.g. GC(-MS), NMR, etc.) for the qualitative and quantitative determination of by
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of carrier generation and recombination with different laser pulse specifications Evaluation, documentation and publication of the data obtained in the form of reports, manuscripts and presentations in English
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therefore teams up materialists, electrical engineers, and computer scientists of TUD, RWTH Aachen and Gesellschaft für Angewandte Mikro- und Optoelektronik mbH ( AMO ) in Aachen, Forschungszentrum Jülich
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out within the DFG Priority Programme “DaMic - Data-driven Alloy and Microstructure Design of Sustainable Structural Metals” (SPP 2489), in close collaboration with a research partner responsible for
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system analysis or comparable Initial experience in optimization or statistics is an advantage Initial experience of an object-oriented programming language (e.g. Python, Matlab) and MS Office Analytical
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conferences Requirements: a university degree in the field of computer science, data science, computational modeling or related subjects in combination with civil engineering, transport engineering a strong
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, Management Science, Business Analytics, or a related field. Strong analytical skills with experience in AI, machine learning, or data analytics. Very good English skills in writing and communication
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to impart both scientific and methodological knowledge and offers the opportunity to regularly present doctoral projects in internal events and benefit from scientific exchange. You can find information
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to impart both scientific and methodological knowledge and offers the opportunity to regularly present doctoral projects in internal events and benefit from scientific exchange. You can find information
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biogeochemistry, environmental sciences or a related field is required. Good methodological (theory) knowledge of analytical approaches for measurements of climate-relevant trace gases is required. Knowledge