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-scale nature, complexity, and heterogeneity of 6G networks, we use tools such as artificial intelligence/machine learning, quantum computing, graph theory, graph-signal processing, and convex/non-convex
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Industrial Engineering and Operations Research. Good technical knowledge of probabilistic models and machine learning Basic knowledge of quality management in the manufacturing industry (e.g., SPC, FMEA, HACCP
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Microeconometrics Strong interest in methodological issues in microeconometrics, machine learning, high-dimensional models Proven ability to autonomously conduct research at a post-doctoral level Proven ability
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knowledge of developing AI-based information systems, such as AI-enabled engagement e.g., agentic AI and AI-enabled insight generation e.g., machine learning analytics in both individual and organizational
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innovation practice, in the context of the 3 ECTS course “Soft Skills for Applied Computer Scientists”; You contribute, where relevant, to senior technical and scientific support in ongoing research projects