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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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program across Aalborg and Copenhagen campi. This includes delivering courses in teaching programming e.g. C# and Python, real-time graphics rendering, use of generative AI as well as AI application
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. More information about DESS can be found at: https://www.cs.aau.dk/research/Data-Engineering-Science-and-Systems. The Center for Classical Communication in the Quantum Era (CLASSIQUE) is a pioneering
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challenge: how 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
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. The candidate should ideally have experience or interest in one or several of the following areas: A solid foundation in programming and system development, particularly using Python and machine learning
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learning, data science, atmospheric sciences, geophysics, or related fields. Solid numerical modelling and programming skills (e.g., Python, TensorFlow, scikit learn) are essential, along with a basic
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Experience with scientific programming (e.g. in python) Experience with modelling of disordered materials is seen as an advantage Experience with automated computational workflows is seen as an advantage
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, Grasshopper, Python). Explore new trajectories for the advancement of AI-supported integrated architecture and its potential impact on the build environment. Contribute to developing open-source tools and code
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communications, fundamental knowledge on computing architectures, and advanced programming skills (e.g., Python, C++, Matlab/Octave). Experience with simulation, emulation, and modelling tools for signal
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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