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molecular biologists, MDs, PharmDs, tumor immunologists, stem cell biologists and computational scientists – at all career stages. Our multidisciplinary approach gets inspiration from the fields of immunology
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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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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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, 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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-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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-supervisors, as well as with other doctoral students and postdocs in the supervisors’ lab. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological
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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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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
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together with their supervisors, as well as with other doctoral students and postdocs in the supervisors’ groups. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence
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need to fulfil the following requirements: PhD in one of the following fields: bioinformatics, molecular biology, computer science or related subjects the employer considers of relevance to the position