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, experimental physics or a comparable discipline Experience in instrumental analytical chemistry Knowledge of hydrogen and energy research is an advantage Experience in the practical application of GC-MS methods
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. through an extensive range of training courses; a structured program of continuing education and networking opportunities specifically for doctoral researchers via JuDocS, the Jülich Center for Doctoral
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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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strengths, e.g. through an extensive range of training courses; a structured program of continuing education and networking opportunities specifically for doctoral researchers via JuDocS, the Jülich Center
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-edge Machine Learning applications on the Exascale computer JUPITER. Your work will include: Developing, implementing, and refining ML techniques suited for the largest scale Parallelizing model training
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on investigating the change in the catalysts surface under relevant process conditions using spectroscopic analysis methods. Your task will include: Application of established and novel methods for the preparation
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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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have very good knowledge of energy technology, energy economics, and energy policy You have already gained initial experience in energy system modeling You are confident in object-oriented programming
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quantum information Experience with programming, preferably with Python Fluent speaking and writing skils in English Team-oriented and highly motivated to work in an experimental laboratory A background in
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-oriented way of working A distinct advantage would be: Experience with data analysis and scientific programming (e.g. Origin, Igor Pro, Python, Matlab, Mathematica) A good command of written and spoken