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Experience in deep learning/generative AI or molecular modelling Prior research or industrial exposure Ability to work in a multidisciplinary and collaborative environment How to apply: The application
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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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information. The techniques include image registration, segmentation, and regression/classification, often include deep learning-base implementations. Together with experts in epidemiology, genetic, and multi
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influencing drug efficacy and safety. The project addresses a major bottleneck in drug discovery—metabolite identification, which is traditionally time- and resource-intensive. By leveraging deep learning
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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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, 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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students and 200 postdocs will be part of the Research School. The DDLS program has four strategic research areas: cell and molecular biology, evolution and biodiversity, precision medicine and diagnostics
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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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. 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