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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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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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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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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
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grades in the field of mechanical engineering, material science, physics, computational science or similar, with experience in modeling and simulation Strong understanding of the (computational) mechanics
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(UTC) Type of Contract To be defined Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research
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. INDUSTRY COLLABORATION: Benefit from direct integration into a science-industry collaboration with practical relevance HIGH-PERFORMANCE COMPUTING: Leverage cutting-edge computational resources, including