21 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "University of Waterloo" PhD positions at University of Luxembourg in Luxembourg
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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 subject of the thesis will be “Exploring Large
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-FNR PEARL Research Grant in the area of Information Systems Engineering, and, depending on interest, in fields, such as Generative AI & Machine Learning, Data Privacy, Cyber Security, Digital Identities
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understand, explain and advance society and environment we live in. Your role The University of Luxembourg invites applications for a fully funded Ph.D. position in machine-learning force fields (MLFFs
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administrations, including eBus Competence Center, Emile Weber, GomSpace, Gradel, IEE, Nexxtlab, Telindus, and Ville de Luxembourg. For more information on the ATLAS IPBG Programme, see here: https://edu.lu/wwpy7
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factors. The LCSB recruits talented scientists from various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently
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Website https://www.aplitrak.com/?adid=UmVjcnVpdGluZy4yNzMwNy45OTA4QHVuaXZlcnNpdHlvZmx1… Requirements Research FieldEducational sciencesEducation LevelMaster Degree or equivalent Additional Information Work
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machine learning, deep learning, or computer vision Experience with Python and common AI frameworks (PyTorch, TensorFlow) Interest in hallucination detection, robustness, trustworthiness, and (optionally
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, MONAI) Strong interest in image analysis / computer vision and pattern recognition, including but not limited to biomedical applications Strong interest in applied machine learning, including but not
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. The LCSB recruits talented scientists from various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work
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framework to bridge this gap and enable organizations to confidently deploy secure GenAI solutions by evaluating the machine-learning models intrinsically, identifying components of an AI pipeline and their