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(Stockholm, Sweden) and the candidate will benefit from a strong (inter-)national network of collaborators in protease biology and computational proteomics. The successful candidate for this position will join
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life science technologies with data and AI expertise. Computational methods and artificial intelligence applied to large-scale molecular data are transforming the study of biological systems at all
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data on our dedicated high-security compute cluster Miarka at UPPMAX, as well as on local servers. Automation of data handling and integrating systems for laboratory tracking (samples, steps, reagents
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program 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 cellular processes
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universities. SciLifeLab forms an internationally unique infrastructure and research community, bringing together groundbreaking life science technologies with data and AI expertise. Computational methods and
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and evaluation of novel treatment strategies and application of computational approaches to analyse omics data. Our experimental and translational studies are carried out in close collaboration with
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for the PLP Strategic Area. Key responsibilities may include: Contributing to the overall scientific direction and strategic development of the PLP program, including developing a long-term vision from
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-performance computing. SLU provides access to extensive datasets that can be used to develop machine learning methods and automated analyses relevant to the position. Long-term datasets are available from, i.a
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Do you want to contribute to top quality medical research? Join our pioneering AI designed cyclic peptide engine project at Karolinska Institutet and SciLifeLab, where we are revolutionizing drug discovery by integrating artificial intelligence with synthetic biology to target “undruggable”...
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School of Electrical Engineering and Computer Science at KTH Project description Third-cycle subject: Computer science This project involves generative modeling to address missingness in mass