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Learning with Graphs led by Prof. Nils M. Kriege. Our research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains
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analyse and develop new, well-founded methods and learning algorithms that extend the boundaries of existing techniques - for example, with respect to expressivity, generalization, interpretability
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research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains from chem- and bioinformatics to computer vision and
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in Physics, Mathematics, Computer Science or a closely related field, ideally with a strong focus on quantum computing and numerical simulations. • Experience in data-reuploading quantum algorithms
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quantum algorithms, optical quantum computing and quantum machine learning (highly desirable). • Experience in machine-learning schemes based on arrays of nonlinearly interacting mechanical oscillators