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fundamental knowledge about the handling and capturing of flow behavior in multistage compressors. The collaborative frame with a prestigious industry partner will give insight to future technology requirements
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, C++, etc.) Knowledge of machine learning, data mining, or related fields Excellent communication skills and ability to work in a collaborative team environment Interest in social science research
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or microfluidics and ideally in quantitative data analysis. As a theoretical candidate, you have knowledge in quantitative biology, soft matter/complex systems physics or statistical physics. You enjoy working in
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Master’s degree in biotechnology, bioengineering, biosystems engineering, chemical engineering, food science, or a comparable field of study, preferably with an affinity for technical tasks - Basic knowledge
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analysis (TEA) or an affinity towards these research questions. - Basic knowledge in bioprocess design, bioengineering and/or mathematic modeling - Affinity towards research question in life cycle
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from a university with a focus on aerospace, physics, or related fields • Very good and fundamental knowledge in the areas of theoretical fluid mechanics and structural mechanics, as well as aero-thermal
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well as knowledge representation and inference. In the research project DrawOn, new technologies for analyzing 2D digital drawings and reconstructing 3D building models will be developed. The goal of this project is
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03.06.2021, Wissenschaftliches Personal The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and
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03.06.2021, Wissenschaftliches Personal The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and
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mathematics, (theoretical) computer science, machine learning foundations, electrical engineering, information theory, cryptography, statistics or a related field. - Advanced knowledge of probability theory