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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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and develops a wide range of topics related to chemical hydrogen storage along the entire process chain. We place a particular emphasis on LOHC technology, addressing issues across different scales. Our
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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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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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Infrastructure? No Offer Description Work group: IAS-9 - Materials Data Science and Informatics Area of research: Promotion Job description: Your Job: You will strengthen the data science and machine learning
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information from experiment data Evaluation and development of specialized and/or interpretable machine learning approaches for the domain of materials science, physics, microscopy Incorporation of machine
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thesis. Your Profile: Successfully completed Master`s degree in the field of materials science, engineering, physics or chemistry or a similar field Very good knowledge in the field of solid-state
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: Successfully completed Master`s degree in the field of materials science, engineering, physics or chemistry Very good knowledge in the field of solid-state chemistry and materials engineering Experience in
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Profile: Masters degree in physics, materials science, physical chemistry, electrical engineering and related disciplines Very good grades in the masters and bachelors degrees are mandatory Knowledge
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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