👋 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.
🎓
Defended my Ph.D.! Open to new roles
PhD in machine learning & computational biology | Open to research scientist & postdoc positions
- Paris, France
-
20:00
(UTC +01:00) - https://gjhuizing.github.io/
- @gjhuizing
- in/gjhuizing
Pinned Loading
-
cantinilab/stories
cantinilab/stories PublicLearning cell fate landscapes from spatial transcriptomics using Fused Gromov-Wasserstein
Python 9
-
cantinilab/Mowgli
cantinilab/Mowgli PublicSingle-cell multi-omics integration using Optimal Transport
-
CSDUlm/wsingular
CSDUlm/wsingular PublicPython package for the ICML 2022 paper "Unsupervised Ground Metric Learning Using Wasserstein Singular Vectors".
Python 9
-
cantinilab/OT-scOmics
cantinilab/OT-scOmics PublicThis 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.
Something went wrong, please refresh the page to try again.
If the problem persists, check the GitHub status page or contact support.
If the problem persists, check the GitHub status page or contact support.