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learning, etc.); · Knowledge of explainable AI and Knowledge Graphs with ontology (e.g., RDFS, OWL); · Demonstrated experience with common advanced signal processing techniques (e.g. denoising
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and advancing techniques such as machine learning, graph-based network analysis, and synthetic data generation, the project tackles key challenges in anomaly detection, transaction classification, and
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one-fits-all model was proven unsuccessful. Large Language Models (LLMs) and knowledge graph models are expected to harmonize the formats and semantics but there are many open questions about their
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familiarity with fundamental concepts) in several of the following topics: Signal processing for wireless communication. Solid background in optimization and information theory. Good understanding