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evolution across different genomic regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods and statistical analysis (https://cgrlab.github.io
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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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-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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methods. More about the department’s activities can be found at www.medsci.uu.se . The SNP&SEQ Technology Platform at IMV is part of the SciLifeLab National Genomics Infrastructure (NGI) in Uppsala. We
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, lineage-tracing, and computational approaches to address clinically relevant questions in cancer and drug development. Our work is carried out in close collaboration with national and international partners
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School of Engineering Sciences in Chemistry, Biotechnology and Health at KTH Job description The Affinity Proteomics unit (https://www.scilifelab.se/facilities/affinity-proteomics/ ) is part of
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University. As a doctoral student, you will be trained in a scientific approach. In short, you will be trained to think critically and analytically, to solve problems independently using the right methods, and
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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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located at SciLifeLab in Stockholm , in direct connection with NGI Stockholm . Description of the DDLS Fellows program Data-driven life science (DDLS) uses data, computational methods and artificial
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analysis and computational modelling. This position offers the opportunity to contribute to innovative experimental research within a dynamic and collaborative environment, advancing high-impact studies