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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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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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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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design for resource allocation or distributed systems Solid mathematical and analytical skills. Experience in scientific programming (e.g., Python, MATLAB, or similar). Demonstrated ability to publish
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systems, integrated sensing and communication, and theoretical modeling of 6G systems Solid mathematical background and significant experience in scientific computing programming (MATLAB, Python, C/C
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. Experience with digital twin modelling and validation of energy system solutions will be an advantage. Strong programming skills in Python, MATLAB or similar environments are required, and it will be advantage
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, e.g., in Python, PyTorch, TensorFlow, or similar. Curiosity to work with researchers from a heterogeneous group, with core expertise in communication theory, networking, information theory, statistics
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skills, with the ability to bridge theory and experimental data Experience with computational tools such as MATLAB, Python, and multiphysics simulation platforms (e.g., COMSOL, Ansys) Motivation to engage
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. Proficiency with CST Studio Suite, HFSS, and related full-wave EM simulation workflows. Competence in MATLAB or Python for numerical modelling, data analysis, and optimisation. Ability to conduct experimental