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(TUM), Campus Heilbronn. We seek exceptional candidates excited about graph drawing, network visualization, and information visualization. The specific research focus can be chosen by the applicant based
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the ANR. PhD student in Graph Signal Processing for the Characterization of Multipolar Electrograms of Persistent Atrial Fibrillation. Responsible for a significant proportion of brain strokes, atrial
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. Project details In this project we aim to develop graph deep learning methods that model spatial-temporal brain dynamics for accurate and interpretable detection of neurodegenerative diseases
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queries within embedded knowledge graphs. It will involve designing or adapting efficient indexing structures tailored for vector databases and exploring hybrid neurosymbolic techniques to enhance query
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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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Josip Juraj Strossmayer University in Osijek School of Applied Mathematics and Informatics | Croatia | 25 days ago
, scientific field of mathematics, for work on the project Croatian Science Foundation „Metric properties of graphs“ (Project ID: DOK-2025-02-1688), according to the tender Croatian Science Foundation „Razvoj
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are looking for a highly motivated and skilled PhD researcher to work on structural surrogates of offshore wind foundations through graph-based machine learning. Our goal is to perform full-structure
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embedding graph-based problems, particularly those known to be challenging for classical computing architectures. Some of your responsibilities will include: Design and develop mixed-signal circuits
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) have some exposure to (hyper)graph theory, network science, and/or reaction mechanism/CRN studies. Candidates who do not meet all of these criteria should not feel discouraged. If you are interested in
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methods to make them usable for transparent energy systems analyses. The collected data will be processed and semantically enriched using methods you develop before being transferred to a knowledge graph