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PhD Position in Theoretical Algorithms or Graph and Network Visualization - Promotionsstelle (m/w/d)
of Munich (TUM), Campus Heilbronn. We are looking for exceptional candidates who are interested in pursuing a PhD in either theoretical computer science or graph and network visualization. We seek PhD
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Dortmund, we invite applications for a PhD Candidate (m/f/d): Multidimensional Omics Data Analysis You will be responsible for Setup a knowledge graph in neo4J for microbiome research Integration
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computer science with very good results - Interest on topics around the area of distributed systems and data management - Basic knowledge in distributed systems and graph algorithms is desired - Hand-on experience
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starting date is November 2025. The topic of the PhD project will be theoretical research in discrete optimization, with a particular focus on either graph algorithms or multiobjective optimization
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science and industry. With the Open Research Knowledge Graph (ORKG ), we are working to revolutionise the exchange and use of scientific knowledge in the digital age. The Technische Informationsbibliothek
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collaboration with experimental groups, to address questions of biomedical or industrial relevance. The candidate will develop and use machine learning methods (mainly graph neural network architectures
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which are funded by the federal and state governments. The research institutes belong to the Leibniz Association. WIAS invites applications as PhD Student Position (f/m/d) (Ref. 25/11) in the Leibniz
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institutes in Berlin which are funded by the federal and state governments. The research institutes belong to the Leibniz Association. WIAS invites applications as PhD Student Position (f/m/d) (Ref. 25/11) in
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WIAS Berlin, Weierstrass Institute for Applied Analysis and Stochastics Position ID: 2306 -PHD [#26752, 25/11] Position Title: Position Location: Berlin, Berlin 10117, Germany [map ] Appl Deadline
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to understand, predict, and treat diseases. You will work with multimodal biomedical datasets including omics, imaging, and patient data and apply cutting-edge AI models such as graph neural networks, transformer