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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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on an exciting Wellcome-Trust funded project. The research focuses on decoding neural representations across dynamic brain states through advanced computational analysis of large-scale neural recordings. What you
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are seeking a motivated research assistant to join our team working on an exciting Wellcome-Trust funded project. The research focuses on decoding neural representations across dynamic brain states through
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representation and knowledge graphs; programming skills in Python and knowledge of relevant NLP libraries (e.g. spaCy, Hugging Face Transformers); good English communication skills and an interest in
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synthesis. In particular, we aim to develop process knowledge bases to support generative methods and, secondly, to develop a tool for determining the optimal structure of any type of thermodynamic cycle by
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established techniques for quantum circuit representation and manipulation (e.g. diagrammatic methods like ZX-calculus) towards description of quantum noise employ such extended methods for quantum circuit
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leveraging visual perception of human actions, object properties, and scene context. It integrates machine learning tools, knowledge representation, and robot actions design to develop decision-making
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, multimodal AI, or knowledge representation is also advantageous. Experience of collaboration with industry is a plus. Knowledge of Swedish language is considered a merit. Rules governing PhD students are set
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tackles fundamental challenges in multimodal representation learning by developing novel approaches to align distinct embedding spaces from speech and sign language modalities. Sign languages encode
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of Prof. Dr. Frank Cichos and Dr. Nico Scherf (Max Planck Institute for Human Cognition and Brain Sciences). The position is part of a collaborative project in the Center for Scalable Data Analytics and