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science. The successful candidate will develop innovative methods and models to decode the language of the genome and advance our understanding of how genetic variation contributes to complex diseases
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, bioengineering, or related life sciences) Strong organizational skills and the ability to manage multiple tasks and projects in parallel Hands-on experience with experimental laboratory work (e.g. cell culture
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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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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 infectious biology to
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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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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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Data Driven Life Science (DDLS). About the DDLS Fellows program Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and 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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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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methods. Good computer skills. Meriting Qualifications Documented theoretical or practical experience in structural biology and/or mass spectrometry. Experience in project management and communication with