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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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. You would be welcomed in the the Yant Lab (https://www.yantlab.net/ ) Using large-scale graph-based pangenomics and forward evolutionary simulations, the student will develop predictive models
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interdisciplinary environment. The research engineer will be based at SciLifeLab (Science for Life Laboratory) Stockholm & KTH, Department of Gene Technology, and will be supervised by Associate Professor Stefania
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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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services allowing integration of large language models, foundation models focused on life science data, and narrow models in complex research workflows (for example, through AI agent architectures
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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