34 parallel-computing-numerical-methods PhD positions at University of Luxembourg in Luxembourg
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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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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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21 Aug 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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, consider the usage of standards, and contribute to standardisation documents Present findings at international events The research activities will be hosted by the Parallel Computing and Optimisation Group
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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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society. For more information, please visit our website: https://www.uni.lu/snt-en/research-groups/finatrax/ The person will pursue a Ph.D. degree (Doctorate) in computer science and information system
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Pathogenesis in the age of the microbiome (MICRO-PATH; https://micro-path.uni.lu ) is a highly competitive, interdisciplinary, research-intensive PhD training programme, supported by the PRIDE
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associated threats. The research project of the PhD student will thus focus on defining methods to track, monitor, and manage the use of GenAI. While this can rely on recentely proposed telemetry framework
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) - Three-dimensional conformally flat Lorentzian manifolds through experimentation (Karin Melnick) - Representation-theoretic methods in algebraic geometry (Karin Melnick & Pieter Belmans) - Computational
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computational models and data analysis code to process large, multimodal behavioral datasets using both traditional methods (e.g., factor analysis) as well as more modern approaches (e.g., deep learning