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16.07.2025, Wissenschaftliches Personal A PhD position (75% TV-L E13, to be extended to 100% after 8 months) in discrete optimization is available at the Professorship of Optimization and
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data to answer relevant questions and solve real-world problems. It brings together fundamental, methodologically driven research in optimization, machine learning, and artificial intelligence with
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PhD Position in Theoretical Algorithms or Graph and Network Visualization - Promotionsstelle (m/w/d)
geometry, algorithmic complexity, and combinatorial optimization. Our contributions are regularly published in top venues like the Conference on Artificial Intelligence (AAAI), the Symposium on Algorithms
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main focus on the development of control software. ▪ You will design and implement advanced control and readout protocols and optimize experimental characterization workflow,s leveraging machine learning
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decision-making in operational settings, aiming to enhance performance and optimize decision processes. Collaboration opportunities with industry partners are available, providing a strong mix of academic
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-dimensional endwall flow structures in blading of modern axial compressors in a multi-stage environment, with an emphasis on flow topology, loss mechanisms, and strength of occurrence. - Investigation
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should enable the corresponding production processes and environments to be automatically initialized, processing areas to be generated and the optimal processing tools and their alignment to be assigned
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network adaptation is crucial for optimal perfusion. In living systems, network architecture constantly changes in response to environmental stimuli towards uniform flow to optimize transport. Combining
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technology, and process optimization using mathematic modeling - Evaluate modified growth factors under real conditions with medium recycling - Independent work on research projects - Close cooperation with
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TEA of a defined process for cultivated meat with material cycling - Optimize the process, also applying mathematic modeling, to improve yield and sustainability - Independent work on research projects