19 computer-programmer-"Multiple"-"Prof" PhD scholarships at University of Luxembourg
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Health. METAMIC 3 is funded by the European Commission under the Horizon Europe framework programme (Grant Agreement number 101225682). The METAMIC 3 project will embed Doctoral Candidates (DCs) in a
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Application Deadline 21 Aug 2026 - 08:31 (UTC) 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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extended from cloud solutions (such as OpenLLMetry), the research question is how to identify anomalies in collected information that can come from multiple AI services either invoked manually by users or by
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of computer science, cryptography. All positions are fully funded for up to 4 years. Candidates should have (at the beginning of the contract but not necessarily at the time of application) a Master's degree in
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to evaluate. The main research question is how to automatically harmonize the retrieved information allowing a unique analysis and to map them against multiple user-tailored outputs. This is necessary as the
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. For more information, please visit our website: www.uni.lu/snt-en/research-groups/finatrax/ Candidates will be enrolled in the PhD program in Computer Science and Computer Engineering with
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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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). This project aims to accelerate the energy transition in Luxembourg by co-creating an ambitious research program. It will utilize a data-driven approach to support decision-making for an optimal energy system
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& Applications. The "Technical Standardisation for Trustworthy and Sustainable ICT, Construction, and Aerospace" research programme represents a strategic collaboration between Luxembourg Institute
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). This project aims to accelerate the energy transition in Luxembourg by co-creating an ambitious research program. It will utilize a data-driven approach to support decision-making for an optimal energy system