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PhD Position in Theoretical Algorithms or Graph and Network Visualization - Promotionsstelle (m/w/d)
interfaces. Topics of interest include: Planar and geometric graph algorithms Approximation and parameterized algorithms Clustering, embeddings, and structural graph theory Computational complexity and
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, these models often use simplified, linearized assumptions, limiting their capacity to capture the nonlinear complexities inherent in real-world hydrological processes. Recently, there has also been the branch
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& Emergent Behaviour in Complex Networks“. Here, we intend to investigate how structural properties of complex networks influence information and opinion dynamics. Our goal is to gain a deeper understanding of
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& Emergent Behaviour in Complex Networks“. Here, we intend to investigate how structural properties of complex networks influence information and opinion dynamics. Our goal is to gain a deeper understanding of
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information theory. An ideal candidate would also have knowledge of quantum mechanics of complex systems. Formal hiring requirement is a master degree in physics, computer science, or an equivalent degree
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. The position is within the Math+ project "Information Flow & Emergent Behaviour in Complex Networks“. Here, we intend to investigate how structural properties of complex networks influence information and
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– from the modeling of material behavior to the development of the material to the finished component. PhD Position in Machine Learning and Computer Simulation Reference code: 50145735_2 – 2025/WD 1
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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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“Light- versus electron-induced spin-state switching of complexes on insulating layers” within the Priority Programme SPP 2491 “Interactive Spin-State Switching” This DFG-funded project aims
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– depending on the successful candidate’s background and interests. Your tasks: Develop new exact and approximation algorithms and perform complexity analyses for optimization problems on (temporal) graphs