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Apply for this job See advertisement About the position Integreat – the Norwegian Centre for Knowledge-driven Machine Learning at the University of Oslo – invites applications for a postdoctoral
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the Digital Signal Processing and Image Analysis Group, Section for Machine Learning, Department of Informatics. You will be part of Visual Intelligence and the DSB group. For more information about the
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representations developed in them as a foundation for this research activity. In this project, you will develop fundamental machine learning methods and apply them in an interdisciplinary research environment
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rapidly. As the amount and value of business processes based on mobile digital technologies increase, so do the amount and severity of cyber threats. Both defenders and attackers are now using Machine
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language processing or computational linguistics; alternatively, in computer science or machine learning with a specialization in natural language processing Documented knowledge of core machine learning methods and
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profile for their ideal candidates are described as follows. PREMAL is a project focused on privacy-preserving machine learning using FHE. The project will investigate trade-offs between accuracy, time, and
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, causal inference, and machine learning to study real-world treatment patterns, effectiveness, and safety of monoclonal antibodies (mAbs) used in autoimmune, inflammatory, and neurological diseases. Using
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interdisciplinary research group of Risk and Stochastics and the Community of SURE-AI . The positions are mostly intended within the areas of stochastic analysis and computational methods towards machine learning
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over the parameter space) without specifying a model nor a prior. Such methods can in principle be applied to machine learning algorithms in order to get uncertainty estimates for parameters governing
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, smartphone penetration exceeds 80%. The automatic transport mode detection (TMD), when effectively exploited, possibly using some kind of machine learning algorithm, provides more accurate data than