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independently. Merits: Education or training in computer vision, machine learning, deep learning, bioinformatics, advanced microscopy, cell biology, or RNA biology. Education in mathematical statistics
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of polyploid genome evolution across contrasting timescales. The student will receive interdisciplinary training in bioinformatics, evolutionary genomics, and high-performance computing within the DDLS data
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systems across scales, from molecular processes to ecosystems. The DDLS program aims to train the next generation of data-driven life scientists and build internationally leading computational capabilities
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artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab and Wallenberg National
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Biostatistics (MEB). The group studies biological mechanisms, risk factors, and resilience processes underlying health and disease during aging, with a particular focus on preclinical dementia and cardiometabolic
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level in computational biology, physics, applied mathematics, computer science, bioinformatics, structural biology, or a related subject or completed courses with a minimum of 240 credits, at least 60 of
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to receiving your application! Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and
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, and industry, combining biology, physics, and chemistry to advance our understanding of structure and dynamics in biological processes. Access to advanced equipment and expertise in lipid chemistry