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good results - Interest on topics around the area of distributed systems and data management - Basic knowledge in distributed systems and graph algorithms is desired - Hand-on experience with large-scale
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to work in an interdisciplinary environment. Desirable Skills: Experience working with or supporting a scientific facility/instrument platform. Knowledge of graph-based methods, manifold learning
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project, we are looking for a strong candidate to contribute to the development of quantum algorithms and applications, focusing on quantum walks and quantum machine learning on graph structures. Your
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science and industry. With the Open Research Knowledge Graph (ORKG ), we are working to revolutionise the exchange and use of scientific knowledge in the digital age. The Technische Informationsbibliothek
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research contributions will include designing algorithms for concept and structure extraction, building neural/graph hybrid models for pedagogical reasoning, implementing ontology-alignment methods for cross
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Max Planck Institute for Astrophysics, Garching | Garching an der Alz, Bayern | Germany | 2 months ago
. Project Description The successful candidate will work on the development of a Gaussian Process regression framework on graphs and its integration into: the Numerical Information Field Theory (NIFTy
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framework for AI in gynecological oncology. We integrate symbolic knowledge representation (Ontologies/Knowledge Graphs) with Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) to create