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new methods incorporating transformer models, graph neural networks, and self-supervised learning approaches that can extract deeper biological insights from genomic data. Join us in this exciting
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mathematics, or a related area. The ideal candidate has strong familiarity with several of the following subjects: algorithmics, mathematical modelling, graph transformation, algorithm engineering. Applications
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Physics, Spectral Theory, Quantum Chaos, Large Graphs and Quantum Walks. Related areas such as Quantum Information can also be considered. This position is offered through the research funds of Mostafa
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curriculum vitae of each nominee (if available, mandatory for self-nominations Please note that any further documents or appendices (like tables, graphs, etc.) will not be considered in the evaluation
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, and biophysical modeling. • Experiment with collaborative research methods, contributing to the lab’s graph-based notetaking and knowledge base. • Explore innovative research dissemination methods
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graphs and digital platforms. For this purpose, we conduct in-house research, cooperate with renowned universities and research associations and maintain an international network. FIZ Karlsruhe is a GmbH