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-based tools in water electrolysis research Collaboration with computer science, catalyst synthesis and characterization, and theory groups to optimize water electrolysis using the knowledge obtained in
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degradation processes in PEM, AEM, and alkaline water electrolysis Implementation of AI-based tools in water electrolysis research Collaboration with computer science, catalyst synthesis and characterization
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papers Contributing to educational events, such as courses and hackathons Your Profile: Excellent Master or PhD degree in Computer Science, Mathematics, Physics, or similar fields Good knowledge of AI and
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this project, you will develop innovative quantum algorithms for the accurate calculation of materials properties. You will combine methods from quantum informatics and solid-state physics to describe
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or computer science Experience with UNIX-like operating systems Mathematical and programming skills (Python, Machine Learning) Basic understanding of molecular forces and structures Excellent knowledge of written and
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, material testing process Your Profile: Excellent masters degree in Chemical Engineering, Materials Science, Data Science, Mechatronics or a similar discipline Strong interest in pursuing research
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Your Job: Your PhD project will be part of an interdisciplinary research project bridging theoretical physics and theoretical computer science. In the course of this, you will work on extending
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bridging theoretical physics and theoretical computer science. In the course of this, you will work on extending established techniques for quantum circuit representation and manipulation (e.g. diagrammatic
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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: Digital methods for inverse materials design are essential
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bridging theoretical physics and theoretical computer science. In the course of this, you will work on implementing efficient simulators for continuous and discrete variable systems with noise based