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for Knowledge-driven Machine Learning. We are looking for a motivated researcher, who has experience with both theoretical, methodological and applied research in change and anomaly detection in sequential data
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properties of the Higgs boson. The group focuses on final states containing several tau-leptons. The analysis activity is now extended to include generic anomaly searches using Machine Learning. Furthermore
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anomaly searches using Machine Learning. Furthermore, the group takes part in ATLAS upgrade, with participation in the ITk-Pixels project, with responsibilities concerning testing and delivery of pixel
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mathematical modelling tools. Excellent knowledge of programming languages such as R, Python, Julia, etc. Familiarity with AI algorithms and Machine Learning Fluent oral and written communication skills in
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/mathematical-cognition-and-literacy . The group collaborates with national and international experts in mathematical cognition, mathematics education, linguistics, and machine learning. Your immediate leader
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Intelligence (AI) and machine learning, digital sociology, AI and the sociology of knowledge, AI and expertise, and digitalization and criminology (digital criminology). A prerequisite for employment is that
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power engineering. In condition monitoring non-invasive data is analyzed through machine learning algorithms or by statistical methods. The aim of predictive analysis is to use non-invasive methods
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such as R, Python, Julia, etc. Familiarity with AI algorithms and Machine Learning Fluent oral and written communication skills in English Desired qualifications: Experience with research on epidemiological
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machine learning. Magnetic Resonance Imaging. Laboratory experience from porous media research related to physics and/or chemistry. Personal and relational qualities will be emphasized. Motivation
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machine learning Personal and relational qualities will be emphasized. Motivation, ambitions and potential will also count when evaluating the candidates. Special requirements for the position