112 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" positions at University of Luxembourg
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technologies that have a positive impact on society. For further details, please visit our website: https://www.uni.lu/snt-en/research-groups/finatrax/ The candidate will support project partnerships with
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We seek a highly motivated AI scientist, biostatistician or computational biologist who is well versed in the statistical and machine learning analysis of biomedical data and bioscientific
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We are seeking a highly motivated Postdoctoral Researcher to join the FNR AI-HPC 2025 BRIDGES project GenePPS, which investigates how machine learning can enable prediction of gene perturbation
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within the project AI4TECS Writing a doctoral dissertation in computer science Publishing research findings in leading international conferences and high‑impact journals in AI, machine learning, and
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experience in the following areas: Applied Machine Learning for Autonomous Systems: Experience developing and deploying ML models for perception, prediction, or decision-making in autonomous driving or robotic
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technologies (fiber-optic sensors, DIC), and computer science (machine learning tools) in collaboration with de department of Physics. The aim of the BriCE project is to develop a novel bridge monitoring
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approaches - such as machine learning, artificial intelligence, or other data-driven methodologies - will be an asset. This position is part of the University of Luxembourg's tenure-track scheme, which offers
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develop machine‑learning models that learn from and build upon these pNTA results. The successful candidate will be supervised by Prof. Dr. Emma Schymanski and Dr. Federica Piras. For further information
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Machine Learning (ML) to detect anomalies (such as a new unknown possible entry point) and provide actionable recommendation according to the recovered attack surface. A tool like AMASS[1] from OWASP
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Validation (Serval) research group and work on a research project related to the application of machine learning for official statistics. The subjects of the research are: AI-assisted Bond Issuance, Causal