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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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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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part of the SciLifeLab and the research school of the Wallenberg National Program for Data-Driven Life Science (DDLS), within the research area Cell and Molecular Biology. To achieve this, the doctoral
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employing a combination of genetics, molecular biology, including Ribo-Seq, RNA pull-down and mass spectrometry, reporter assays in cells and tissues, and computational sequence analyses. This implies to work
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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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sciences Collaboration with experts in lab science, medicine, and machine learning Modern GPU compute infrastructure A chance to contribute to cutting-edge research with real-world impact Who you are Strong
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, the University of Melbourne, and the University of California, Los Angeles. We strive for all PhD students to get a solid international experience during their PhD. About the DDLS Fellows program The PhD position
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Collaboration Conduct research together with academic, industrial, and healthcare partners in a highly collaborative environment. Who we are looking for A highly motivated PhD candidate excited by computational
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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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experimental and computational methods to identify molecular mechanisms leading to dysfunctional cellular states in human disease (www.camunaslab.org ). The candidate will contribute to the improve Slice-seq, a