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, molecular communication, and systemic molecular networks, and to identify how these processes change across physiological and disease states. Through this work, you will develop predictive and biologically
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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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experimental and computational methods to identify molecular mechanisms leading to dysfunctional cellular states in human disease (www.camunaslab.org ). The candidate will contribute to the improve Slice-seq, a
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part of the SciLifeLab and the research school of the Wallenberg National Program for Data-Driven Life Science (DDLS), within the research area Cell and Molecular Biology. To achieve this, the doctoral
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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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systems, neuroscience, and safety and security. The Division of Systems and Control enjoys a wide network of strong international collaborators all around the world, for example at the University of Oxford
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will be affiliated with the national DDLS program, through which you will have access to computing resources, the national DDLS research school, and other training and networking opportunities throughout