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of pancreatic cancer. This group is led by Associate Senior Lecturer Dr. Qiaoli Wang, as part of the SciLifeLab & Wallenberg National Program for Data-Driven Life Science (DDLS) . Group members are enrolled in
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computational methods with a particular focus on deep learning and image analysis. The project relies on a close collaboration with researchers at the Department of Immunology, Genetics and Pathology (IGP
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, or a related field, who enjoys interdisciplinary work spanning wet-lab experimentation and computational data analysis. In addition to the aforementioned requirements for the position: A Master’s
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www.medtech4health.se/aida . AIDA Data Hub, a branch of AIDA, is a national e-infrastructure for research and innovation in data-driven precision health. We provide secure computing and storage resources, data and data
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research group funded by the Data-driven Life Science Fellows (DDLS) program. Led by Wei Ouyang, the group builds next-generation AI systems for cell and molecular biology. Data-driven Life Science Fellows
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The Department of Cell and Molecular Biology (ICM) (https://icm.uu.se) is organized into seven research programs, each focusing on distinct areas within cell and molecular biology i.e. computational
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an outstanding and ambitious postdoctoral researcher in computational biology to pioneer understanding and modeling of tissue architecture using single-cell and spatial transcriptomics data. The focus will be
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of pancreatic cancer. This group is led by Associate Senior Lecturer Dr. Qiaoli Wang, as part of the SciLifeLab & Wallenberg National Program for Data-Driven Life Science (DDLS). Group members will be enrolled
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, animals, fungi, bacteria, etc.). The Program for Plant Ecology and Evolution, where this position is located, is home to eight research group focusing on genomics, adaptation and speciation as well
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and biophysics, at Stockholm university. For more information about us, please visit: www.dbb.su.se . Main responsibilities At the SciLifeLab and Wallenberg National Program for Data-Driven Life Science