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biological data, development of deep learning and large language models for biological discovery or graph-based methods for molecular and cellular networks. The technological foundation further consists
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Wikibase instance Curate and model historical migration datasets within the dedicated Wikibase instance Contribute to the design of ontologies and metadata schemas for the knowledge graph Develop data-driven
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at the Faculty of Mathematics at TUD. Tasks: generation of hyper uniform patterns (point, scalar and vector fields) application of topological data analysis tools such as persistent homology and graph statistics
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: algorithmics, graph transformation and algorithm engineering. Exposure to systems chemistry or systems biology is an asset but not a must. Proven competences in programming and ease with formal thinking are a
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-regulatory networks. Following cis-GRN network reconstruction and formal graph analysis, we will identify key regulatory factors governing cell-type specific response to CMT-causing mutations. Finally, we will
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. The current research topics include disorder effects on phase transitions (diluted ferromagnets, long-range correlated defects, spin glasses, random graphs and networks), long-range interacting systems
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and polyploid crop species and benchmark them against other methods such as graph-based methods. This project will combine algorithm development and computational programming with large population
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). "Statistical field theory applied to complex networks” "Quantum geometrogenesis – Graph theoretic approaches to building spacetime” web page For further details or to discuss alternative project arrangements