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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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17.07.2025, Wissenschaftliches Personal The Chair of Software Engineering & AI is searching for a new doctoral research associate (TVL-E13) in Generative Engine Optimization. Research focus
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representations. • Computational efficiency: Designing adaptive and physics-aware strategies (e.g., optimized residual selection, physics-based zooming) for real-time inference. • Practical usability: Developing
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predictive simulations, real-time control, and process optimization. You will work on the development of deterministic population balance models, conduct single-crystal and batch crystallization experiments
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Researchers: Ph.D. in Computer Science or Mathematics, ideally with a background in one or more of the following areas: Optimization, Game Theory, Machine Learning Applicants must demonstrate: • An excellent
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representations. • Computational efficiency: Designing adaptive and physics-aware strategies (e.g., optimized residual selection, physics-based zooming) for real-time inference. • Practical usability: Developing
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Iterative Algorithms: Optimization and Control.” About the Project The focus of the project is the analysis of iterative algorithms arising from time discretizations of nonlinear evolutions of various kinds
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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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), and joint optimization—impact the model's accuracy, robustness, and generalization capabilities? Can fine-tuning a pretrained model like CLIP on domain-specific data (e.g., automotive or travel-related
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energy use more efficient. We develop new optimization methods, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity