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KTH Royal Institute of Technology, School of Electrical Engineering and Computer Science Job description We are looking for a highly motivated postdoctoral researcher for a joint project between the
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evolution across different genomic regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods and statistical analysis (https://cgrlab.github.io
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Referensnummer IFM-2026-00053 Work assignments This PhD position focuses on methodological and computational development in cryo-electron microscopy (cryo-EM), with emphasis on image reconstruction
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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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, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. The incumbent
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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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-performance computing. SLU provides access to extensive datasets that can be used to develop machine learning methods and automated analyses relevant to the position. Long-term datasets are available from, i.a
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life science technologies with data and AI expertise. Computational methods and artificial intelligence applied to large-scale molecular data are transforming the study of biological systems at all
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contribute new and better ways to analyse and interpret large-scale data. In your position, you will develop computational methods for cryo-EM reconstruction, heterogeneity analysis, and modeling of structural
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methods. More about the department’s activities can be found at www.medsci.uu.se . The SNP&SEQ Technology Platform at IMV is part of the SciLifeLab National Genomics Infrastructure (NGI) in Uppsala. We