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, and how their combination can improve safety signal detection. As a PhD fellow, you will be working with large-scale longitudinal data, managing data, writing scripts, performing statistical analyses
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to machine learning algorithms in order to get uncertainty estimates for parameters governing the distribution of the observed data. The predictive Bayes scheme for uncertainty quantification contains a wide
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in foundational neural models that learn from large unlabeled image datasets, also incorporating context from additional data such as wireline logs or well reports. You are suited for this position
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application development. Deep Learning techniques, Data Engineering, and Semantic Technologies Open-source artificial intelligence, machine learning, statistical estimation methods, software tools, and big-data
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more information see: http://www.mn.uio.no/english/research/phd/ All candidates and projects will have to undergo a check versus national export, sanctions and security regulations. Candidates may be
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samples. Apply machine learning and deep learning techniques to automate segmentation and quantitative analysis of tomographic refractive-index data from cells and tissue samples. Apply the developed
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the researchers from Department of Automation and Process Engineering will play a key role. We welcome motivated applicants in robotics, control, AI, machine learning, physics, and related fields, including early
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Science About the project This PhD project integrates pharmacoepidemiology, causal inference, and machine learning to study real-world treatment patterns, effectiveness, and safety of monoclonal antibodies
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to the successful completion of a PhD degree. For more information see: http://www.mn.uio.no/english/research/phd/ All candidates and projects will have to undergo a check versus national export, sanctions and
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to the successful completion of a PhD degree. For more information see: http://www.mn.uio.no/english/research/phd/ What are we looking for in you? Personal skills: We are seeking a highly motivated, enthusiastic and