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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 top quality medical research? The Strategic Research Programme in Diabetes (SRP Diabetes) at Karolinska Institutet is funding a prestigious fellowship programme for
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integrate different experimental and computational approaches for the completion of the project, including genomics, yeast genetics, high-throughput biology approaches and bioinformatics. The candidate will
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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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at the Science for Life Laboratory (SciLifeLab) and the position is funded by its Data Driven Life Science program (DDLS). Your mission You will develop a deep learning model of the tumor microenvironment (TME) in
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cancer-stroma interactions in pancreatic cancer. The long-term goal of our lab is to enable computer-aided design of precision cancer medicine. The lab is situated at the Science for Life Laboratory
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Professor Cristiana Cruceanu and the Women’s Mental Health Group at IMM led by Associate Professor Donghao Lu. Dr. Cruceanu leads a research program that studies molecular mechanisms of how stress exposures
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the synthesis of functional nanoscale materials and devices for biomedicine using flame aerosol technology. The focus of the research program lies on studying the physicochemical properties of materials made by
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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