Deep Learning Systems for Biomedical Imaging
Bioimage Software Engineer @ Institut Cochin · CNRS · France BioImaging (2024–2026)
MSc Bioinformatics @ Université Paris Cité
Paris, France
profile = {
"role": "Bioimage Software Engineer · ML Systems · Computer Vision",
"focus": ["Computer Vision", "ML Integration","3D Image Analysis", "Biomedical Imaging"],
"status": "Seeking CDI · Bioimage / Computer Vision / Software Enginner · Paris · Sept. 2026",
}I build software systems for biomedical image analysis, enabling large-scale processing and interactive visualization of 3D biological data used daily by researchers on a national imaging infrastructure.
My work sits at the intersection of software engineering and bioimaging, where I integrate computer vision and machine learning methods into production systems rather than standalone research prototypes.
My edge: I write production code and understand the biology behind the data.
Deep Learning & Computer Vision
Scientific Imaging & Bioimage Analysis
Cellpose · StarDist · Ilastik · Huygens · QuPath · ImageJ/Fiji · Bio-Formats · DICOM · OME-TIFF · OME-ZARR
Bioinformatics · Single-Cell · Multi-Omics
BioPython · Scanpy · AnnData · Seurat · DESeq2 · limma · Bioconductor · ComplexHeatmap · fgsea · MODELLER
scRNA-seq · spatial transcriptomics · multi-omics · Matplotlib · Plotly · ggplot2
Software Engineering & Infrastructure
Deep learning pipeline for mammography screening on DICOM data.
Multi-model ensemble (EfficientNet, ConvNext) · medical windowing · class imbalance strategies
PyTorch · pydicom · scikit-image
Protein structure recognition via sequence-structure alignment using double dynamic programming.
Modular architecture (9 core modules) · orchestration pipeline · tested
Python · BioPython
Molecular energy minimization via steepest descent — analytical & numerical gradient approaches.
3D structure visualization · VMD trajectory generation · PDB parsing
Python · NumPy · Matplotlib
Always happy to connect, exchange ideas, or just talk science and code.