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opportunities. What you'll bring Essential Hold a Ph.D. in a relevant field (e.g., Computational Biology, Bioinformatics, Machine Learning, Systems Biology, Genomics, or a related discipline), or be in the final
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. Applicants should hold a PhD in Computational Biology, AI/ML, Computer Science, Population Genetics, Bioinformatics, or a related field, and have fewer than five years of postdoctoral experience. Strong
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work at the interface between computational spatial omics, single-cell mass spectrometry (MS)-based proteomics, multiplex imaging, and bioinformatics. We have recently co-developed Deep Visual Proteomics
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endosymbiotic interactions between soil microbes and crops. The overall aim of the project is to characterize novel signalling processes that enable plant root endosymbiosis. The role: Working as part of a team
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disease. Key responsibilities Lead and conduct the processing and statistical analysis of large-scale long-read RNA and DNA sequencing, single nuclei RNA sequencing and spatial transcriptomics
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to therapeutic discovery You bring PhD in computational biology, bioinformatics, computer science, or related field Strong coding skills (Python required; ML frameworks preferred) First-author publication(s
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, genetics and physiology Experience with bioinformatics and coding in Python or other programing language Experience with protein software tools like AlphaFold3, Boltz2, PyMOL, Chimera, etc. Interest in
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or more of the following areas as demonstrated through at least one first-author publication: machine learning/computer science, computational biology/bioinformatics, cheminformatics. Individuals should
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experience in one or more of the following areas as demonstrated through at least one first-author publication: computational biology/bioinformatics, metabolism/metabolomics, analytical chemistry/mass
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range from cell biological over biochemical to molecular biology and bioinformatics approaches. Collaborations with structural biologists are possible. Your profile Applicants should hold a PhD in