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for Interdisciplinary Digital Sciences (CIDS), the Department for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI Dresden) offers a full-time position as Research Associate / PhD Student (m/f/x) (subject to
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-learning models (e.g., graph neural networks, equivariant architectures) in collaboration with computer science researchers. Applying developed models to problems in Earth and planetary interiors, such as
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, graph theory, graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and supported by the COMMLab, the 6GSPACE Lab, the HybridNetLab, the QCILab
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(R2) Positions PhD Positions Application Deadline 29 Jul 2026 - 23:59 (Europe/Warsaw) Country Poland Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 1 Oct 2026 Is
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differential equations, functional analysis, graph theory or similar areas depending on the evolving needs of the department. The successful candidates are also expected to supervise undergraduate and graduate
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in generating answers in the form of answer maps. You will explore these challenges together with the Principal Investigator as well as a postdoctoral researcher and two PhD candidates. We are looking
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learning, quantum computing, graph theory, graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and supported by the COMMLab, the 6GSPACE Lab
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cloud-based storage and service tools is helpful Preferred Qualifications: MS or PhD in a relevant field Experience with network neuroscience, graph theory, or connectomics Familiarity with high
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-scale nature, complexity, and heterogeneity of 6G networks, we use tools such as artificial intelligence/machine learning, quantum computing, graph theory, graph-signal processing, and convex/non-convex
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NMBU finnes på www.nmbu.no Where to apply Website https://universitypositions.eu/jobs/523633234-phd-position-within-causal-machin… Requirements Research FieldEngineeringEducation LevelMaster Degree