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research contributions will include designing algorithms for concept and structure extraction, building neural/graph hybrid models for pedagogical reasoning, implementing ontology-alignment methods for cross
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. Umeå University is offering a PhD position in Computing Science with a focus on machine learning for graph
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Zerbib. This includes graph theory, discrete geometry, topological combinatorics, extremal combinatorics, and flag algebras. The position has a 2-1 teaching load and a requirement to be involved with
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the design and analysis of such models. PhD position 1 will focus on developing new graph-theoretic frameworks for analyzing graph learning models, such as Graph Neural Networks or Graph Transformers. PhD
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) Positions PhD Positions Application Deadline 10 Mar 2026 - 12:00 (Europe/Dublin) Country Ireland Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 May 2026 Is the job
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) Positions PhD Positions Application Deadline 10 Mar 2026 - 12:00 (Europe/Dublin) Country Ireland Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 May 2026 Is the job
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) Positions PhD Positions Application Deadline 20 Mar 2026 - 18:00 (Europe/Berlin) Country Germany Type of Contract Temporary Job Status Part-time Is the job funded through the EU Research Framework Programme
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has a strong PhD program in Applied Mathematics, Applied Statistics, Graph Theory/Combinatorics, and Analysis, featuring active research collaborations both within the University and with external
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; distributionally robust optimization; 2) Graph Neural Networks, Large Language Models (LLMs), and geometric deep learning; and 3) federated learning and privacy preserving computing. Basic Qualifications Candidates
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/or Korte), 3. Conformal deformations of metric measure spaces and/or general regularity and convergence for graph-based machine learning using stochastic game theory and theory of metric spaces (with