Senior Researcher in AI Based Foundation Models for Cardiometabolic Disease

2 weeks ago


København N, Denmark KU-SUND-Metabolismecentret Full time

KU-SUND-Metabolismecentret seeks a highly motivated and dynamic researcher to join our team as a postdoctoral research fellow. The successful candidate will have expertise in developing deep learning methods for multi-modal data integration, particularly with experience in large-scale human genomics and multi-omics datasets.

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The Rasmussen Group at KU-SUND-Metabolismecentret focuses on development and application of computational algorithms such as machine and deep learning for analysis and integration of multi-omics and multi-modal data within cardiometabolic disease. We develop supervised, un-supervised, self-supervised and generative models to learn across multiple types of data rather than treating each data modality in isolation.

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As a postdoctoral research fellow, you will work on developing patient-level foundation models (PLUMs) using EIR, our deep learning framework for integrative multi-modal data analysis. You will apply these models to large-scale genomics and multi-omics datasets from biobanks such as UK Biobank and Danish national health registries.

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  • You will develop and optimize foundation models using our EIR framework
  • Implement various deep learning architectures for multi-modal data integration
  • Analyze genomic and multi-omic data, evaluate model performance, and generate interpretable predictions for downstream applications in patient stratification and precision medicine

We are looking for a highly motivated and enthusiastic scientist with 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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