Summary
Eric Audemard is a scientific data analyst and bioinformatician with over a decade of experience turning large, noisy omics datasets into actionable biological insights. He designs efficient algorithms, scalable pipelines, and reusable tools—publishing open-source projects like EPCY and KM—and has led the development of an interactive data platform that bridges biologists and computation. His career spans academic and industry roles in cancer and immunology research, contributing to a Discovery of the Year–recognized publication and production-grade analyses of terabyte-scale sequencing data. Comfortable across Python, R, C++, cluster orchestration (SLURM) and web stacks (Vue.js/Flask), he focuses on resource-efficient solutions that prioritize reproducibility and interdisciplinary collaboration.
11 years of coding experience
Master's degree, Informatique & Math, Master's degree, Informatique & Math at University Montpellier II
Research Doctorate, Bioinformatics, Research Doctorate, Bioinformatics at université paule sabatier
École d'hiver francophone en apprentissage profond, deep learning, fomation, École d'hiver francophone en apprentissage profond, deep learning, fomation at HEC Montréal
Post-doc, Bioinformatics, Post-doc, Bioinformatics at McGill University
French, English