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spatial immune cell niches in cancer. Advances in high-throughput spatial omics technologies measuring various analytes now capture this complexity in remarkable detail, providing groundbreaking insights
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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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of polyploid genome evolution across contrasting timescales. The student will receive interdisciplinary training in bioinformatics, evolutionary genomics, and high-performance computing within the DDLS data
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tissues or cells at cohort scale have documented proficiency in High Performance Computing (HPC).Practical experience running large-scale jobs on an HPC cluster, including CPU large-memory node management
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diversity of high-quality education and world-leading research in several fields. Notably, the groundbreaking discovery of the CRISPR-Cas9 gene-editing tool, which was awarded the Nobel Prize in Chemistry
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diversity of high-quality education and world-leading research in several fields. Notably, the groundbreaking discovery of the CRISPR-Cas9 gene-editing tool, which was awarded the Nobel Prize in Chemistry
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Development Design new statistical and machine learning models tailored to this emerging omics modality. Multimodal Data Analysis Work with high-dimensional datasets combining quantitative RNA features
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to receiving your application! Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and
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science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and
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of LNPs under various storage conditions, the aim is to develop formulations with both high performance and improved stability. The work includes the design and systematic screening of LNP formulations