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hampers our ability to establish causal relations between molecular alterations and disease phenotypes. In this PhD you will address this by developing a deep learning model of cancer. The PhD position
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Sintorn, Professor in digital image processing, at the Department of Information Technology and conducted alongside researchers developing computational methods with a particular focus on deep learning and
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computational methods with a particular focus on deep learning and image analysis. The research is done in close collaboration with the BioImageInformatics Unit of SciLifeLab . SciLifeLab is a national resource
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spectrum, in topics in virology and immunology, and currently specializes in computational biology focusing on developing methods and applications of deep learning for protein sequence and structure, as
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on applying AI and machine learning to molecular design challenges. This position is one of several industrial PhD roles funded by the DDLS program, which supports training in four strategic areas: cell and
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, within the Centre for Image Analysis at the Department of IT and conducted alongside researchers developing computational methods with a particular focus on deep learning and image analysis. The project
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. The long-term goal is to enable targeted interventions for the right individuals, based on their lifestyle, disease trajectories, and molecular profiles. To achieve this, we will apply deep learning models
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, and will apply deep learning to integrate the analysis flows. The PhD student will develop the method and apply to numerous in-house samples of environmental sequences, pushing the boundaries of RNA
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learning, deep learning and relevant software framework (R and Python) is highly desired. Very good oral and written communication skills in English are required. Emphasis will also be given on personal
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of MSI advances our understanding of complex brain processes. The prospective PhD candidate collects brain MSI data and develops novel machine learning methods in connection to generative models such as