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collaborators in computational biology, machine learning, and imaging-based profiling. The position involves leading independent research projects at the interface of machine learning and biology, with a strong
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well as be technically responsible for the selection-based projects. Your tasks will be to develop expression and purification protocols for challenging target proteins in our drug discovery projects, as
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offers two tracks: • Academic track (15 positions) hosted at Swedish universities or the Swedish Museum of Natural History • Industry track (7 positions) hosted by life science companies based in Sweden
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responsible for designing, optimizing, and fabricating these systems using bioprinting and cleanroom-based techniques. You will also measure molecular signatures and isolate cell subsets of particular interest
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and evolutionary dynamics. The positions are based in Assistant Professor Lisandro Milocco’s research group at Stockholm University and SciLifeLab, within Sweden’s national Data-Driven Life Science
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developed the SPARCED pipeline to convert structured lists of species, parameters, and reaction types into an SBML (Systems Biology Markup Language) model file, and we created a model based on one
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Taheri Lab and the Lundberg Lab, funded by the Digital Futures (DF). The position is based at KTH Royal Institute of Technology and SciLifeLab (Science for Life Laboratory). KTH is Sweden’s largest
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program based in Sweden that been systematically mapping the localization of human proteins in cells, tissues and organs during the past 20 years. For this project, we map the subcellular distribution
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. Copy of diploma from your PhD. Translations into English or Swedish if the original documents have not been issued in any of these languages. Your complete application must be received at KTH no later
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, and ERC Consolidator grant (DETOXPEST) and aims to establish a public, cross-species “pan-terminome” knowledge base of plant proteoforms and to uncover how conserved proteolytic processing