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machine learning-based software applications for materials science Develop code and utilize machine learning to support the automation of characterization and fabrication processes Ensure the integration
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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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addition to technical models allowing to assess technical scaling and an optimal operation. The optimal plant design is identified by considering the energy supply system, the choice of capture technology, the DAC
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data collection and metadata extraction protocols to enhance machine learning-based software applications for materials science. Your Profile: Master’s degree in Engineering, Computer Science, Physics
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/electronic engineering, computer science, computer engineering, physics, and related fields. For IC projects a strong electronics background, with experience in design and simulation of analog, digital
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plant design is identified by considering the energy supply system, the choice of capture technology, the DAC-plant’s technical design, the DAC-plant’s operational concept and the positioning of the DAC
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. Additionally, enjoyment of teamwork is an important requirement. Masters degree in electrical/electronic engineering, computer science, computer engineering, physics, and related fields. For IC projects a strong
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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
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, chemistry, environmental sciences or a related field with good final grade (German system equivalent 2.0 or better) Very good experimental skills are essential Experience with AirCores, GC systems, Balloon