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with Prof. Olivares-Mendez and Dr. Carol Martinez, the members of the Space Robotics (SpaceR) research group (www.spacer.lu ) and Redwire Space Luxembourg (https://redwirespace.com/ ). The group works
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conducts research on the application and the impact of digital technologies like DLT/Blockchain, Digital Identities and Machine Learning/AI on organisations from both the private and public sectors
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, Reasoning and 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
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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
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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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Multi-omics data integration and workflow improvement Development and application of machine learning-based algorithms for the identification of antibiotics-associated proteins and antimicrobial
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technologies, biophysics, soft and living matter, photovoltaics, spectroscopy, and machine learning. DPhyMS fosters a collaborative spirit through partnerships with all faculties at Uni.lu, national research
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and advancing techniques such as machine learning, graph-based network analysis, and synthetic data generation, the project tackles key challenges in anomaly detection, transaction classification, and
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proof-of-concept software tools Machine learning is a plus Strong analytical and programming skills are required (Python, Matlab, and C/C++). Prior proven experience in data-driven innovation projects is
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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