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together with their supervisors, as well as with other doctoral students and postdocs in the supervisors’ groups. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence
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parts of the research, in particular, statistical analyses of data and manuscript writing. You may also be involved in supervising PhD students, contributing to project management, and assisting other
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the Medical Faculty and the Institution for Clinical Sciences Lund University in Malmö. The group consist of 3 PhD students, 2 postdocs and does research on various aspects of anesthesia and intensive care
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postdocs will be part of the Research School. The DDLS program has four strategic research areas: cell and molecular biology, evolution and biodiversity, precision medicine and diagnostics, epidemiology and
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Assessment, or other closely related fields, or who has a degree from another country that is equivalent to a doctorate in the mentioned subjects, qualifies for the position. In accordance with the postdoc
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Assessment, or other closely related fields, or who has a degree from another country that is equivalent to a doctorate in the mentioned subjects, qualifies for the position. In accordance with the postdoc
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, implement, and maintain reproducible bioinformatics pipelines. The work may also include statistical analyses and data visualization to identify and interpret somatic mutational patterns and other genomic
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health. Visit https://www.umu.se/forskning/grupper/interactive-and-intelligent-systems/ for more information. Project description and work tasks We are seeking a candidate for a 3-year postdoc position
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investigators across three faculties with Professor Lars Nyberg as the project leader. The postdoc will be based within the Department of Computing Science and work closely with both the Department of Statistics
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covers areas such as pure mathematics, applied mathematics, mathematical statistics, as well as computer vision and machine learning. The department has approximately 150 employees, including 21 full