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Field
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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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of Mathematics, Section for Statistics and Data Science, invites applications for a PhD fellowship in statistics. We are looking for a motivated candidate, with a deep interest in mathematical statistics, with a
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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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with data linkage and working with routine healthcare data Experience with machine learning or AI applications in healthcare settings Advisory or consultancy experience Understanding of implementation
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results in foundational neural models, where models learn from large unlabelled image datasets, but also on additional data like clinical reports or electronic health rec-ords. The work will be done in
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multiple sources of data describing ecological dynamics. The PhD project will address the following aims: 1) Develop efficient tools for learning about models from data, 2) incorporation of expert knowledge
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refractive-index imaging of complex samples. Apply machine learning and deep learning techniques to automate segmentation and quantitative analysis of tomographic refractive-index data from cells and tissue
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, New York 14850, United States of America [map ] Subject Areas: Data Science / Statistics , Applied Mathematics , Artificial Intelligence , Bayesian Statistics , Big Data , Scientific Machine Learning
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equations, stochastic control and filtering, stochastics for data analysis and machine learning. These areas will be prioritized. The focus is on the development of original mathematical methods for AI and
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% position is available at the University of Agder, Faculty of Engineering and Science as a PhD Research Fellow in ICT, affiliated to the Department of Information and Communication Technology at, for a