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, computational modelling, bioinformatic analysis, and experimental vascular biology. Based in a dynamic translational research environment of data-driven life science, computational imaging, and vascular surgery
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Networks. The project encompasses several challenges in the gene regulatory network (GRN) field, from simulating realistic networks and data to accurate inference of GRNs from noisy gene expression data
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informatics. This, to serve the biological goal of mapping out the breast cancer tumor microenvironment, understanding the regulatory signaling network, and identifying early stage progression markers and
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program (Data-Driven Life Science) with focus on precision medicine. Access to top-level infrastructure, a new therapy development initiative for brain diseases (CNSx3), and a strong network spanning
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networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid academic background with thorough computational and
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Are you interested in developing computational tools and learning strategies for understanding health and disease at the microscopic scale? Would you like to be part of a research team with skilled
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of cancer cells. The models are trained on high-throughput datasets, including metabolomics, proteomics, and transcriptomics, and constrained to align with the cell’s molecular networks. This allows us to
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, wildlife management, forestry and crop protection. The Evolving Networks Lab is part of the Insect Ecology unit Read more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about