57 programming-"https:"-"FEMTO-ST"-"UCL" "https:" "https:" "https:" "https:" "https:" "P" research jobs in Luxembourg
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2027 - 04:15 (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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- 02:52 (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 staff
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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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2027 - 01:36 (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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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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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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programming for projects on neurological diseases. The candidate should have experience in the analysis of large-scale biomedical data (omics, clinical or other large-scale biological data), using statistical
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The Department of Finance at the University of Luxembourg invites students to apply for Doctoral researcher positions in Finance. The program follows the standard international format with rigorous
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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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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