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Join MultiD Analyses AB and the University of Gothenburg to develop innovative bioinformatics and machine learning methods for RNA Fragmentomics, with the ambition to improve cancer care through
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signaling and function. As such, they also play decisive roles in cardiovascular disease, chronic kidney disease, cancer and chronic inflammatory disease. These diseases affect 33%, 60%, 10% and 33
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adaptation to changing physiological demands. Understanding these principles will provide new insights into how genome instability arises in human disease, including cancer. The successful candidate will join
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data, and apply the computational methods to understand biomedical problems like tumor microenvironment, immunology, and aging. The individual will work with Dr. Yi Zhang (https://yi-zhang-compbio
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initiative that is developing an explainable and interoperable multimodal AI system to improve personalized prognoses and treatment decisions for patients with hepato-pancreato-biliary cancers. We integrate
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microenvironment, and other biological processes. Conduct preclinical studies using in vivo disease models (cancer, inflammation, organ injury, etc.) and new alternative methodologies (advanced biological models
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medicine and diagnostics, epidemiology and biology of infection. For more information, please see https://www.scilifelab.se/data-driven/ddls-research-school/ The future of life science is data-driven. Will