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Development Design new statistical and machine learning models tailored to this emerging omics modality. Multimodal Data Analysis Work with high-dimensional datasets combining quantitative RNA features
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. The goal of this project is to advance gene regulatory network (GRN) inference from multi-omics data by developing novel AI techniques that exploit the knowledge of gene perturbations (experimental design
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biomedical engineering, electrical engineering, machine learning, statistics, computer science, or a related area considered relevant for the research topic, or completed courses with a minimum of 240 credits
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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
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. The goal of this project is to advance gene regulatory network (GRN) inference from multi-omics data by developing novel AI techniques that exploit the knowledge of gene perturbations (experimental design
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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