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science, embeddings and software agents is welcomed. The EBU-NEO tech-stack consists of: Python, LangChain, LangGraph, MongoDB, Milvus, Elastic Search. Knowledge from the fields of media science, user
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Andres Masegosa (arma@cs.aau.dk), Department of Computer Science. (please see: https://andresmasegosa.github.io/ . The project’s domain PI is Professor Jamal Jokar Arsanjani (jja@plan.aau.dk), Department
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(https://www.classique.aau.dk). CLASSIQUE will address a suite of fresh research challenges defined by the intersection of digital applications that have real-time requirements and quantum resources
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to evolve classical communication networks to support both traditional data and the unique requirements of quantum information systems (https://www.classique.aau.dk). CLASSIQUE will address a suite of
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to support both traditional data and the unique requirements of quantum information systems (https://www.classique.aau.dk ). CLASSIQUE will address a suite of fresh research challenges defined by
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team. Significant software development experience in several key languages, e.g., Rust, C++, or Python (not MATLAB), algorithms, and machine learning is necessary as well as excellent communication