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you have: Completed university studies (masters degree) and a doctoral degree in computer science, applied mathematics, computational science (physics, math, chemistry,..) and engineering or a related
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the complete chain from materials properties to process design and evaluation. More information on the project can be found here: This specific project (DC7) addresses membrane adsorbers, which have small
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-economically cost-optimal design of a process chain for the production of green hydrogen and methanol, it is necessary to carefully analyze both global and regional demand and to estimate their future
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networks using the numerical simulations Calculating the likelihood of material parameters correctly describing experimental results Correlating material parameters with process conditions of sample
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-scale datasets Implement parallel ML training on the High Performance Computers, including JUPITER, Europe`s first exascale computer Prepare, process and publish datasets and benchmarks for self
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building models Your Profile: Master studies in the field of of mechanical engineering, industrial engineering, process engineering, informatics and mathematics or similar Good knowledge of a programming
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of the Modelica building models Your Profile: Master studies in the field of of mechanical engineering, industrial engineering, process engineering, informatics and mathematics or similar Good knowledge of a
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in physics, physical chemistry, chemical engineering, or related field Knowledge and competences in physical theory and modelling Experience and interest in computer programming Basic knowledge
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) for scientific and large-scale datasets Implement parallel ML training on the High Performance Computers, including JUPITER, Europe`s first exascale computer Prepare, process and publish datasets and benchmarks
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science, physics or a comparable field of study Background knowledge and proven interest in the field of electrochemistry Fluent in spoken and written German as well as English Willingness to get familiar