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dynamical structure directly from time-series data. This includes methodological work on nonlinear state-space reconstruction, system identification, reservoir computing and related recurrent architectures
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identity and extracellular signaling, but how cell types, signaling mechanisms, and transcription factors jointly determine tissue structure is incompletely understood. The Koplev lab is recruiting
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evolution across different genomic regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods and statistical analysis (https://cgrlab.github.io
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on biological processes as well as the impact of biological processes on materials. Our ambition is to foster a dynamic teaching and research environment that is internationally recognised for its excellence in
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structures in inflammatory diseases and cancer. The successful candidate will join a growing collaborative research group, who works closely with researchers in the Department of Gene Technology, SciLifeLab