Postdoctoral Research Fellow in Deep Learning and Multi-Modal Data Integration

4 days ago


København N, Denmark KU-SUND-Metabolismecentret Full time

KU-SUND-Metabolismecentret invites applications for a postdoctoral position in the Rasmussen Group. The group's focus is on developing and applying computational algorithms for analysis and integration of multi-omics and multi-modal data within cardiometabolic disease.

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As a postdoctoral research fellow, you will contribute to the development of patient-level foundation models (PLUMs) using EIR, our deep learning framework for integrative multi-modal data analysis. You will work on implementing various deep learning architectures for multi-modal data integration and analyzing genomic and multi-omic data.

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  • You will develop novel deep learning architectures for integrating multi-modal data
  • Apply these models to large-scale genomics and multi-omics datasets from biobanks
  • Evaluate model performance and generate interpretable predictions for downstream applications in patient stratification and precision medicine

To be successful in this role, you should have a PhD in Bioinformatics, Computer Science, Molecular Biology, or a related field, minimum two years of postdoctoral research experience, and extensive expertise in developing and applying deep learning methods for multi-modal data integration.



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