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perturbation-based GRN inference for single-cell and spatial multi-omics data, to boost GRN quality and add the cell type and tissue heterogeneity dimensions to causal regulatory analysis. A deep learning
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is key. We also take pride in delivering education to enable regions to expand quickly and sustainably. In fact, the future is made here. Are you interested in learning more? Read about Umeå university
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++ or similar) and an interest in quantitative or computational approaches are required. Prior experience with image analysis, machine learning, signal processing, or structural biology is meritorious but not
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perturbation-based GRN inference for single-cell and spatial multi-omics data, to boost GRN quality and add the cell type and tissue heterogeneity dimensions to causal regulatory analysis. A deep learning
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for human tumors and immunotherapies. The Piazza laboratory (Piazza Lab) uses mass spectrometry-based approaches to study protein interactions in cell and tissues with proteomics. In this project you will
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. You would be welcomed in the the Yant Lab (https://www.yantlab.net/ ) Using large-scale graph-based pangenomics and forward evolutionary simulations, the student will develop predictive models
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universities, as well as a key centre of intellectual talent and innovation. We are Sweden’s largest technical research and learning institution and home to students, researchers and faculty from around the