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technical needs for user experiments, an electrochemical microscope will be implemented, to reach high imaging resolution and a great flexibility concerning various electrochemical environments. Main Tasks
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a paradigm shift in materials science by embedding mechanistic AI agents into physical experimentation cycles-enabling rapid, transparent, and reproducible design of advanced electrocatalysts. Main
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approaches, where data storage and processing occur simultaneously at the materials level, inspired by the operation of the brain. This includes research on unconventional computing paradigms, such as
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assisting with in-situ TEM measurements, facilitating cutting-edge research in sustainability and energy fields. Part of the project will also include the development of deep learning frameworks for TEM image
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of inorganic or colloidal synthesis methods. Familiarity with microscopy image processing or quantitative analysis tools (e.g., ImageJ, Python-based analysis) will be valued. Motivation to work at the
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computer-based systems and the preparation of data for inclusion in lab books, presentations and publications. Maintain a hardcopy or electronic lab book · Work in compliance with relevant Health and Safety