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, and European projects on the topic Publish research findings in the prestigious peer-reviewed journals and present at relevant conferences Contribute to different research projects, either coordinating
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working on related topics Participate in teaching and supervision activities, in line with the candidate's profile and interests The research activities will be hosted by the Parallel Computing and
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to investigate the history of Luxembourg's tax regime, its beneficial elements through time as well as the socio-economic context within which this regime/the different regimes through time developed. The project
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by co-creating an ambitious research program. It will utilize a data-driven approach to support decision-making for an optimal energy system, with specific focus on cost-effectiveness, emission
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to state-of-the-art technologies. Access to extensive scientific and transferable skills training programs available through VIB and KU Leuven.The position is available from September 1st, 2026. How to apply
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, Vehicular Communications Experience in system modeling and simulation of communication systems Strong programming skills in MATLAB are required; experience with Python, C/C++, or GPU-based computing is an
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, including hands-on implementation Strong understanding of machine learning models and their development Strong analytical, problem solver, and programming skills for Python and Matlab are preferred Experience
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demonstrators for satellite communication systems Education: Contribute in the teaching activities of the University's Cybersecurity Master program and supervise the scientific research of PhD/Master students
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(SOC) and cyber defence teams Education: Contribute in the teaching activities of the University's Cybersecurity Master program and supervise the scientific research of PhD/Master students Dissemination
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venuesStrong programming skillsSolid mathematical foundation, including linear algebra, probability, statistics, and optimizationBroad and in-depth experience with machine learning algorithms and deep learning