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nature, and the ideal candidates are comfortable with moving outside their field to understand both molecular biology and computational methods. We rely heavily on collaborations with clinicians, which
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projects are multidisciplinary in nature, and the ideal candidates are comfortable with moving outside their field to understand both molecular biology and computational methods. We rely heavily
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Do you want to contribute to improving human health? Per Svenningsson's research group at the Department of Clinical Neuroscience (CNS) is a translational and multidisciplinary research group studying movement disorders, particularly Parkinson’s disease, and depression. We use cellular and...
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. An important part of the project involves analysis of single unit and LFP data and usage of computational frameworks for anatomical annotation and visualization of structural and functional components of brain
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experimental and computational research methods for systems-level analyses of the human immune system. The aim of the team is to understand immune systems’ variation in health and disease and the regulatory
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University of California San Francisco and Berkeley. Your profile You should have: A university degree at Master level in a relevant area Professional experience from working with data engineering for medical
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Research Council. The future of life science is data-driven. Will you be part of that change? Then join us in this unique program! The research group Data-driven life science (DDLS) uses data, computational
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within biomedical science. The department is among the largest of its type in Europe and has especially strong research profiles in psychiatric, cancer, reproductive, pediatric, pharmaco, genetic, and
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experience in ethical appraisals e.g. as part of an advisory board One member must have a PhD in public or global health, health sciences, nursing or similar program. The other member must have a background in
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bioinformatics and epidemiology. Experience in multiomics data analysis, systems biology, register-based studies using advanced computational techniques (e.g., disease pathway or human disease network analyses