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). The project focuses on developing computational models for cancer risk assessment, integrating multiple types of data and risk factors. The main objective is to design and apply machine learning and deep
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on development of novel computational methods with state-of-the-art machine learning for gaining fundamental insights into healthy and diseased human tissues of the heart, cardiovascular system, and
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) training personalized computational models in new contexts, and (iii) studying in-silico clinical intervention strategies. The postdoctoral fellow will have the opportunity to: Learn about computational
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Join SciLifeLab PULSE (Program for future leaders in Life Science) to move your research career forward. Why PULSE? Empowering Diversity in Science: PULSE is committed to fostering diversity and
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, incorporating their own ideas and experience in computer vision, machine learning, and related fields, to further visualization and interpretation of molecular images. Our research environment focuses
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postdoctoral researcher will be involved into discussions within a broad range of fields including computational, medicinal and organic chemistry. Requirements PhD degree in biochemistry or structural biology
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of training in higher education teaching and learning. The purpose of the position is to develop independence as a researcher and to create the opportunity for further development. The postdoctoral position
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(Stockholm, Sweden) and the candidate will benefit from a strong (inter-)national network of collaborators in protease biology and computational proteomics. The successful candidate for this position will join
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. Our research is focused on cell biology, spatial proteiomics and machine learning for bioimage analysis. The aim is to understand how human proteins are distributed in time and space, how this affects
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(SmT), spatial mass spectromety and CellScape in animal and plant tissues. In addition, the postdoctoral fellow will also apply single-cell multiomics. The postdoctoral projects will have a computational