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). The project focuses on developing computational models for cancer risk assessment, integrating multiple types of data and risk factors. The main objective is to design and apply machine learning and deep
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on development of novel computational methods with state-of-the-art machine learning for gaining fundamental insights into healthy and diseased human tissues of the heart, cardiovascular system, and
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, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. The incumbent
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Join SciLifeLab PULSE (Program for future leaders in Life Science) to move your research career forward. Why PULSE? Empowering Diversity in Science: PULSE is committed to fostering diversity and
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biology to pioneer research in immunology using single-cell and spatial transcriptomics data. The focus will be on development of novel computational methods for gaining fundamental insights into healthy
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contribute new and better ways to analyse and interpret large-scale data. In your position, you will develop computational methods for cryo-EM reconstruction, heterogeneity analysis, and modeling of structural
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internationally outstanding research in the life sciences. Project description We seek two highly motivated postdoctoral researchers to develop new mathematical and computational methods for modeling developmental
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, with joint academic–industrial supervision Data-driven life science is a field of research that utilizes data, computational methods, and artificial intelligence to investigate biological systems and
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on bioinformatics analysis of spatial gene expression data as well as other modalities (i.e. microbiome; metabolites, proteins) generated using the Spatial Transcriptomics (ST) method, Spatial metaTranscriptomics
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protein analysis methods Preferred qualifications Experience from biotech/pharmaceutical industry or relevant academic research environment Experience with structural biology, especially cryo-EM Experience