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an outstanding and ambitious postdoctoral researcher in computational biology to pioneer understanding and modeling of tissue architecture using single-cell and spatial transcriptomics data. The focus will be
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to the group’s open-source software, and participation in the supervision of students. A limited amount of teaching may be included (max 20%). Requirements PhD degree in machine learning, computer science
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employees, including 120 teachers and 120 PhD students. Approximately 5,000 undergraduate students take one or more courses at the department each year. You can find more information about us on the
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What you will do Perform research studies and publish in conferences and journals Supervise master’s and/or PhD students to a certain extent Possibility to engage in teaching at undergraduate/master’s
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of the position is method development. We are seeking a postdoctoral researcher to develop next-generation AI models of cellular dynamics, with a focus on scalable neural network architectures that represent
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focuses particularly on understanding how the tumor microenvironment (TME) undergoes architectural remodeling – including changes in extracellular matrix composition, tissue mechanics, and spatial
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collaboration with experimental LNP PhD / PostDoc projects in the Barriga Lab and with M. Carroni at the Cryo EM facility SciLifeLab. Other responsibilities may include teaching, supervision and contributions
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good software engineering habits — modular, well-documented, reproducible code. Are comfortable working in interdisciplinary teams and can communicate effectively across computational and experimental
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experience and track record in using open databases and bioinformatic tools and services. Strong programming skills for developing computational tools or data workflows (Python or similar), with good software