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excellence as evidenced by strong scientific publications and track record relative to career stage. Strong programming skills (Python or R) and familiarity with high-performance computing Preferred
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of the largest pan-cancer signaling models in the literature. SPARCED is compatible with high-performance and cloud computing, can simulate thousands to millions of single-cell trajectories, is easily expandable
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cutting-edge, high-density data-driven research that impacts academia, industry, and policy worldwide. About the Programme Fellowship: each participant will benefit from a 36-month postdoctoral training
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stage. Strong programming skills (Python or R) and familiarity with high-performance computing Exceptional collaborative abilities Preferred qualifications A doctoral degree or an equivalent foreign
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scientific computing in high-performance computing environments are essential. Excellent written and spoken English skills are required. We are also looking for someone with experience with 3D image processing
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large-scale, high-dimensional datasets including multi-modal data integration and hands-on experience with high-performance computing (HPC) environments Ability to work independently and in
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research platform SciLifeLab Drug Discovery and Development . The Department is also responsible for several student courses and offers high-quality education at both undergraduate and advanced levels
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to certain cells. We use high throughput sequencing to monitor the selection process and discover individual candidates that work well. Our lab is based in Scilifelab, an interdisciplinary research environment
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division The Division of Biomedical Engineering is part of the Department of Materials Science, and Engineering at the Ångström Laboratory. We perform research within the development of miniaturized
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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