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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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. 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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/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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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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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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) in chemistry, materials science, geoscience, physics or related field Experience in laboratory work, e.g. synthesis and/or physicochemical characterization such as IR, CHN, PXRD High motivation
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of materials science, engineering, physics or chemistry or a similar field Very good knowledge in the field of solid-state chemistry and materials engineering Experience in preparation / fabrication
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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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project meetings with the involved partners from industry and research Your Profile: Successfully completed Master`s degree in chemistry, materials science, physics or a comparable field of study Background
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reaction phenomena in nanoporous electrocatalytic materials Collaboration with partner groups in a German–Canadian research project Your Profile: M.Sc. degree in physics, physical chemistry, chemical