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nitrides. You will use synchronized HiPIMS processes to tune the properties and performance of the films. The experiments will be informed by in-situ surface and interface analysis. Your work will make use
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dedicated researcher with a PhD in mathematics, electrical or mechanical engineering, computer science or a related field, and a strong methodological background in machine learning. The ideal candidate has
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transfer at the liquid-solid interface. To connect materials to devices, you will prototype booster-bed reactors from mL to L scale by 3D printing and support the transfer of promising formulations toward
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of competitive funding. Your profile We seek a highly motivated and dedicated researcher with a PhD in mathematics, electrical or mechanical engineering, computer science or a related field, and a strong
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-solid interface. To connect materials to devices, you will prototype booster-bed reactors from mL to L scale by 3D printing and support the transfer of promising formulations toward scalable, solvent-free
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of cooperative effects in charge transport, proton dynamics and electrochemical conversion in solids and at electrochemical interfaces. Your tasks The research focuses on experimental investigations and theory
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and highly interdisciplinary research environment, bringing together expertise in theory, nanoparticle science, OLED technology, and organic chemistry. You will work closely with two ongoing PhD
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-matter interactions, development of automated AI/ML systems for novel materials processing and quality insurance. The lab combines additive manufacturing, large scale laser micro-processing, multiscale
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motivated team player who thrives in a collaborative and interdisciplinary research environment. The ideal candidate possesses a PhD degree in chemistry or chemical engineering, materials science, physics
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with other 2D and 3D techniques such as H&E and LSFM. The work will be done in close cooperation and synergy with an already running PhD project. Partly existing database will be used and extended