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• Information-theoretical analysis of entanglement-supported classical communication, • Encoding protocols for entanglement-assisted classical communication, • Protocols for interleaving transmission in networks
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hosts. The project is centered on the integration and analysis of multiomics datasets utilizing advanced machine learning approaches and biological network analysis. The successful candidate will join an
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large scientific collaborations by applying methods from social network analysis, large language models (LLMs), and knowledge graph technologies. As part of a small, supportive research team, you’ll have
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science Very good knowledge of English or German (spoken and written) Good communication skills, both verbal (e.g., demonstrated by presentations at international conferences) and written (ability
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academic, clinical, and industry partnerships, as well as global networks, we translate biological insights into innovations for early detection, individualized therapies, and disease prevention. Founded in
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a unique opportunity to contribute to cutting-edge research on remote robotic control under network uncertainties, focusing on the development of fault-tolerant and adaptive control architectures
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Excellent command of advanced statistical methods, such as network analyses, using the R programming language Strong publication record relative to the career stage, demonstrating research excellence and
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-university research institutes in Germany. PRIF is headquartered in Frankfurt and has a branch office in Berlin. More than 100 employees from research, administration and science communication contribute
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achievements • very good track-record of research and publication activities, preferably on an international level in one of the following areas of management: Organization, strategy, alliances and networks
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transformations as per the United Nations Sustainable Development Goals (SDGs), through scholarly research, effective networking, and dedicated teaching. The Faculty of Humanities and Cultural Studies