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, manage infrastructure as code, and troubleshoot source code. If you have a solid foundation in Unix/Linux and are ready to dive into complex technical challenges, then you are the one we are looking
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or advanced statistical methods, to help explore molecular, imaging, clinical and/or epidemiological data. You will apply, adapt and develop machine learning approaches to provide data analysis support to data
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dimensional structures of proteins impact codon choices in coding genes. The recruited doctoral student will develop methods to broadly study patterns of codon usage across organisms and apply large scale
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deadline is 30 July 2025. Work task You will provide researchers with expertise in the planning and performance of electron microscopy (EM), electron tomography and image analysis, in medical, biological
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deadline is 30 July 2025. Work task You will provide researchers with expertise in the planning and performance of electron microscopy (EM), electron tomography and image analysis, in medical, biological
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experience. Strong skills in experimental design and software development. “Reproducible research” and “FAIR data” are central concepts to us, and expertise in the development of reproducible code by using
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, including high-throughput screening, high-content imaging, omics technologies, and computational approaches, to elucidate mechanisms of toxicity. Ultimately, our work contributes to a deeper understanding of
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SciLifeLab. To be successful in this position you need a deep understanding of the emerging research field virtual cells, at the interface of advanced molecular cell biology and imaging on the one hand and
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, and expertise in the development of reproducible code by using code sharing platforms, workflow languages and container solutions is a strong merit. Consideration will also be given to how
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. SciLifeLab Lund is comprised of a consortium of nine advanced research infrastructures, with a broad spectrum of focuses that include genomics, proteomics, imaging, structural biology, pharmacological