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gender equality and diversity as a strength and an asset. Description of the workplace The Department of Immunotechnology conducts research ranging from advanced technology development to biomedical
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on methodological development in cryo-electron microscopy (cryo-EM), particularly in image reconstruction and 3D volumetric analysis of macromolecular structures. Rather than aiming to incrementally optimize existing
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, with emphasis on robustness, generalization, and performance in high-dimensional and noisy biological datasets. See this publication for additional details: https://doi.org/10.1111/ede.12449 . The second
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supports projects across four strategic research areas: Cell and Molecular Biology, Evolution and Biodiversity, Precision Medicine and Diagnostics, and Epidemiology and Biology of Infection. The program
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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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of Medical Biosciences, which offers an international, collaborative, and open-minded research environment. Please visit the lab’s webpage for more information: https://erdemlab.github.io . The Erdem research
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mutations in ageing by measuring somatic mutation rates in honeybee castes and experimental evolution lines of seed beetles. Quantifying somatic mutations on a genome scale with high fidelity is
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. Active participation in major international consortia. Support for career development, conference travel, and long-term academic progression More information: https://www.scilifelab.se/researchers/simon
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on bioinformatics analysis of spatial gene expression data as well as other modalities (i.e. microbiome; metabolites, proteins) generated using the Spatial Transcriptomics (ST) method, Spatial metaTranscriptomics
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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