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calculus, gradients, stochastic optimisation, conditioning. Discrete mathematics and graph theory. Typed and attributed graphs and hypergraphs, subgraph matching and isomorphism, graph rewriting
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into insight). To tackle this, the research blends ideas from knowledge graphs, stream processing, database theory, logic, edge and cloud computing, and Artificial Intelligence into a single coherent framework
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. During the PhD, you will work on topics at the intersection of probabilistic and extremal combinatorics, structural graph theory and algorithms. We study problems on discrete structures such as graphs
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follow specialized training programs (e.g. ARENA). Specific Requirements Knowledge: Linear algebra, probability and statistics. Graph theory and algorithms on graphs. Machine learning and deep learning
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in applied mathematics, with interest in both theoretical concepts and practical methodologies. Specific knowledge in at least one of game theory, optimization, control theory, dynamical systems, graph
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22 Jul 2026 Job Information Organisation/Company University of Twente (UT) Research Field Mathematics » Probability theory Mathematics » Statistics Researcher Profile First Stage Researcher (R1
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combination of theoretical research and the implementation of new statistical methodology and thus requires good knowledge of probability theory and mathematical statistics. Many real-world applications exhibit
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, linear algebra, probability theory, (Bayesian) statistics, optimization and elementary graph theory Familiar with machine learning and deep learning Programming experience (Python or Julia) and their
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programmatic activities. Requirements: Ph.D. in computer science, machine learning, biomedical engineering, computational neuroscience, applied mathematics, computational or mathematical sciences, or a related