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gene expression profiles and cellular heterogeneity within tissues can predict how existing drugs might act on previously uncharacterized disease mechanisms or cellular subtypes. These models will be
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variability in risk factor susceptibility, treatment response, disease pathogenesis, and clinical diagnosis (biostatistics, machine/deep learning), ii) Investigating causal processes and disease mechanisms
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. The project will develop fundamental theory and tools that will be key for understanding biological mechanisms causing diseases that are due to gene dysregulation, such as cancer. The core of the project is a
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supported by the SciLifeLab and Wallenberg National Program. The research group at the Department of Medical Biochemistry and Microbiology where the candidate will be joining is focusing on mechanisms and
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molecular mechanisms that drive its invasive behavior, both general and patient-specific. Using cutting-edge spatial techniques and CRISPR-based methods, we build data-driven models that link gene regulation