133 computer-"https:"-"APOS-UFFICIO-CONCORSI-DOCENTI" "https:" "https:" "https:" "J. F" positions in Luxembourg
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may refer to https://www.uni.lu/snt-en/research-groups/sigcom/ . The successful candidate will conduct research on quantum MIMO systems, focusing on the development of theoretical models, communication
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, modelling and implementation of security protocols with classical, post-quantum, and quantum cryptography. For further information, you may refer to https://www.uni.lu/snt-en/research-groups/apsia
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23 Oct 2025 Job Information Organisation/Company University of Luxembourg Research Field Computer science » Computer systems Researcher Profile First Stage Researcher (R1) Country Luxembourg
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5 Jan 2026 Job Information Organisation/Company Luxembourg Institute of Science and Technology Research Field Computer science » Informatics Researcher Profile First Stage Researcher (R1) Positions
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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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through the EU Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you passionate about research? So are we! Come
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that positively impact society. For more information, please visit our website: https://wwwen.uni.lu/snt/research/finatrax/ . The candidate will be funded through an industry partnership with Luxembourgish Leader
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citizens in their choices, public authorities in their decisions and businesses in their strategies. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute
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job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Temporary contract | 14
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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
PhD candidate to develop and apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular