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Uppsala University, Department of Information Technology Are you interested in developing new image analysis and machine learning methods for precision medicine and clinical decision support? Would
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technologies for medical diagnostics, treatment, and monitoring. Our research activities span computational modeling, algorithm development (using both traditional signal processing and machine learning
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approach that integrates wireless communication, computer vision, and machine learning to optimize PC transmission from sensors to an edge server for remote registration. The research is funded by Wallenberg
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information. The techniques include image registration, segmentation, and regression/classification, often include deep learning-base implementations. Together with experts in epidemiology, genetic, and multi
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using machine learning”. The main task of the doctoral student is to carry out an individual research project under supervision. The doctoral position will contribute important expertise in data analysis
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well as the clinical activities at the Karolinska University Hospital, unique access to international expertise in machine learning, state-of-the-art imaging, diverse patient cohorts, and relevant computational
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academia and industry. Requirements The following qualifications are required: Solid knowledge in mathematics and statistics, in areas such as linear algebra, probability theory, machine learning, high
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Wiberg is “Innovative statistical and machine learning methods for comparing performance and outcome in register data studies”, with overall aim to develop, evaluate, and implement innovative statistical
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This is a broad call for five fully-funded PhD positions in computer science and engineering to work on machine learning, autonomous systems, software engineering, formal methods, and network
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of small cryptic plasmids in the development and spread of antibiotic resistance, and ii) Use machine learning tools to examine the complex interplay between bacterial hosts, various plasmids and resistance