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higher education credits (ECTS). Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural networks, as well as courses in Python, GPU programming
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multi-omics integration with advanced machine learning, including artificial neural networks, to predict disease-relevant splice variants across cardiometabolic diseases. By leveraging extensive meta
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the genetic material, and how it interacts with various kinds of micro-organisms. Using this knowledge, we try to elucidate the causes of diseases, and find new ways to diagnose and treat them. The Institute is
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science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and
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is part of the national research programme DDLS. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels
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analysis to better understand how molecular and cellular processes are coordinated across cells, tissues, and organ systems in human health and disease. You will be responsible for developing and applying
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insights on long-standing questions on sex chromosome evolution and on evolutionary processes at large. Duties In this PhD project, you will explore some of the most fascinating questions in evolutionary
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for the position: Experience with mammalian cell culture and associated techniques. Experience in high throughput sequencing. Experience in custom processing of high throughput sequencing data. Experience in
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processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) aims
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data-driven diagnostics. About the project Cancer treatment often involves surgery, chemotherapy, and radiotherapy. While these treatments have improved outcomes, they can be long-lasting and cause