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describing experimental results Correlating material parameters with process conditions of sample preparation Deriving insights for film and device fabrication based on the above described workflow Your
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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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interpretable machine learning approaches for the domain of materials science, physics, microscopy Incorporation of machine learning results with simulation methods Working on project-related tasks where you can
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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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to educational events, such as university lectures, JSC courses and hackathons. Your Profile: Excellent Master in Computer Science, Mathematics, or Physical Science, Very good knowledge and proven skills with
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the overall design Your Profile: Master’s degree in the field of natural sciences, engineering, or a related field of study Knowledge of energy process engineering is an advantage Huge interest in energy
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visit to France. Your tasks will mainly include the: Use of state-of-the-art synthesis processes for the production of graphene oxide-based active materials Optimization of the process to achieve
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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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the: Use of state-of-the-art, industrially established (continuous) synthesis for the production of Na-based cathode active materials Optimization of the process to achieve the highest possible yield and
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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