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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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. 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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– 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
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Your Job: The main objective of this PhD project is to achieve a better understanding of the efficient propulsion of trypanosomes through complex crowded environments, mimicking biological tissues
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focus on eye tracking Collaborating closely with partners from computer science (IAS-7, RWTH) Presenting your work at psychological and interdisciplinary conferences Publishing your findings in scientific
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms