38 computer-science-quantum "https:" "https:" "https:" "https:" PhD positions at University of Luxembourg
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The SnT is seeking a Doctoral Researcher to support the research and development work within the SEDAN group (https://www.uni.lu/snt-en/research-groups/sedan ). We seek a candidate with expertise
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The SnT is seeking a Doctoral Researcher to support the research and development work within the SEDAN group (https://www.uni.lu/snt-en/research-groups/sedan ). We seek a candidate with expertise
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diverse backgrounds (e.g., economics, computer science, information systems, engineering, etc.), united in pursuit of sustainable solutions that positively impact and shape a low-carbon economy and society
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The successful candidate will join the CritiX research group (https://www.uni.lu/snt-en/research-groups/CRITIX/ ) headed by Prof. Marcus Völp. The team focuses on critical information
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The SIGCOM research group, headed by Prof. Symeon CHATZINOTAS, carries out research activities in the telecommunication and networking systems, including NTNs and quantum communication
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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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unique training environment to advance microbiome science through metaproteomics. The program addresses One Health challenges by integrating research on microbial mechanisms, microbiome dynamics in various
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group with broad research competences and interests, with expertise covering mathematics, engineering, computer science and social sciences. We offer excellent working conditions in an international and
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computer science, engineering, information systems, economics, management, law, and other fields, united in pursuit of sustainable technologies that positively impact society. For more information, please visit our
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(supervisor) The position holder will be required to perform the following tasks/will do research on the following topics: Software engineering practices for machine learning Tabular machine learning Large