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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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. The Departments share advanced technological platforms, enjoy both basic and applied research across all kingdoms of life, and have access to national facilities such as SciLifeLab and Swedish high-performance
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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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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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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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, 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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The SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS) invites applications for 22 postdoctoral fellowships starting in autumn 2026. This call marks the launch of a new
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postdoctoral researcher will be involved into discussions within a broad range of fields including computational, medicinal and organic chemistry. Requirements PhD degree in biochemistry or structural biology
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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