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embedded in the Doctoral Programme in Complex Systems Science at the University of Luxembourg. The modelling approaches developed in this project share conceptual similarities with adaptive network and
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backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services
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computational models that describe how trees exchange carbon, water and nutrients with the soil through adaptive root and fungal networks. The successful candidate will design and implement a modelling framework
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research program that brings together physics, chemistry, and machine learning. Your research tasks will include: Uncertainty Estimation in Deep Neural Networks for MLFFs Implement and test uncertainty-aware
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aspects of machine learning focusing on efficiency, generalization, and sparse neural networks. Currently we are expanding our expertise by applying our theoretical findings also to robotics. Hybrid is our
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2027 - 01:44 (UTC) Country Luxembourg Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services & Applications. Your role We offer a fully funded PhD student position within the Trustworthy Software Engineering (TruX
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2027 - 11:23 (UTC) Country Luxembourg Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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Within the frame of the FNR-CORE funded project ENER-G (Empowering Networks of E-buses for Resilient and Green mobility), a doctoral research project is framed. The PhD topic is around and