NGS data analysis · Statistical data analysis · Multi-omics integration · Machine Learning · Reproducible pipelines

• 🧬 9+ years of experience in high-impact research environments
• 📊 Expert in statistical modeling, data integration, visualization, and machine learning applied to high-dimensional biological data
• 📄 Author or co-author of 25+ peer-reviewed articles in journals
• 📫 Reach me at valentin.voillet@gmail.com

Programming & Tools

• R (expert) — statistical modeling, ML workflows, tidyverse
• Python (intermediate) — data manipulation
• HPC / SLURM job scheduling

Bioinformatics Software & Frameworks

Single-cell analysis

• Seurat, Scanpy, scran/scater
• scVI-tools ecosystem (scVI, totalVI, MultiVI)
• Leiden/Louvain clustering, doublet detection (scDblFinder, DoubletFinder)

Multi-omics integration

• MixOmics, MOFA/MOFA+
• WGCNA / co-expression network analysis

Bulk RNA-seq & differential expression

• DESeq2, edgeR, limma
• STAR, RSEM, CellRanger (alignment/quantification)

Flow & mass cytometry

• flowWorkspace, CytoML, flowCore, CATALYST

Workflow & reproducibility

• Nextflow
• Git/GitHub for version control

Statistical Modeling

• Linear & mixed-effects models, GLMs, multivariate analysis, exploratory data analysis

Machine Learning

• Supervised & unsupervised learning, predictive modeling
• Clustering (k-means, Leiden), dimensionality reduction (PCA, UMAP, t-SNE), feature selection

Bioinformatics & Data Types

• Bulk RNA-seq, single-cell RNA-seq, CITE-seq
• Multi-modal data integration
• Flow cytometry

• Ph.D., Computational Biology & Applied Biostatistics — INRA Toulouse / CSIRO St Lucia / INP Toulouse, Université de Toulouse (2016)
  • Awarded Prix Léopold Escande 2016
• MSc, Bioinformatics & Systems Biology, with high distinction — Université Paul Sabatier, Toulouse (2013)