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🎓
Defended my Ph.D.! Open to new roles
🎓
Defended my Ph.D.! Open to new roles

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@ComputationalSystemsBiology

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gjhuizing/README.md

👋 I recently completed my PhD in machine learning and computational biology (September 2024) under the joint supervision of Laura Cantini at Institut Pasteur and Gabriel Peyré at ENS PSL. My research focused on leveraging optimal transport techniques for analyzing single-cell multiomics data, bridging the fields of machine learning and genomics. I am now seeking research scientist or postdoctoral opportunities where I can apply my expertise in machine learning to advance genomics and computational biology.

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  1. cantinilab/stories cantinilab/stories Public

    Learning cell fate landscapes from spatial transcriptomics using Fused Gromov-Wasserstein

    Python 9

  2. cantinilab/Mowgli cantinilab/Mowgli Public

    Single-cell multi-omics integration using Optimal Transport

    Python 37 2

  3. CSDUlm/wsingular CSDUlm/wsingular Public

    Python package for the ICML 2022 paper "Unsupervised Ground Metric Learning Using Wasserstein Singular Vectors".

    Python 9

  4. cantinilab/OT-scOmics cantinilab/OT-scOmics Public

    This Python package will allow you to replicate the experiments from our research on applying Optimal Transport as a similarity metric in between single-cell omics data.

    Python 37 7