Role Overview
As a Bioinformatician, you will play a pivotal role in developing and optimizing bioinformatics pipelines for
transcriptomic data analysis, with a specific focus on Bulk RNA-seq and Single-Cell RNA-seq. You will transform
raw sequencing data into meaningful biological insights to drive translational research and regenerative medicine.
Location: Paris
Key Responsibilities
Pipeline Development & Data Processing
Design, implement, and optimize robust bioinformatics workflows for NGS data analysis.
Manage the end-to-end analytical process for Bulk RNA-seq and Single-Cell RNA-seq datasets.
Ensure the reproducibility, scalability, and efficiency of developed pipelines.
Perform Quality Control (QC) on raw sequencing data.
Execute sequence alignment against reference genomes or transcriptomes.
Generate and manage count matrices and normalized datasets.
Apply preprocessing procedures and batch-effect corrections when required.
Statistical Analysis & Biological Interpretation
Conduct statistical analyses to identify differentially expressed genes (DEGs) using industry-standard tools.
Perform functional enrichment and pathway analysis using key databases (e.g., Gene Ontology (GO),
KEGG, Reactome, GSEA, Enrichr, or similar).
Translate computational results into relevant, actionable biological evidence.
Generate advanced data visualizations to facilitate result interpretation (including heatmaps, volcano plots,
clustering analysis, UMAP, t-SNE, and custom reports).
Multi-Omics Integration & Collaboration
Integrate transcriptomic data with other multi-omic layers, including:
ATAC-seq and scATAC-seq
Quantitative proteomics
Other multi-omic datasets
Contribute to uncovering the molecular mechanisms regulating cellular states, pathological processes, or
regenerative pathways.
Document all analyses meticulously and draft comprehensive technical reports.
Collaborate closely with biologists, data scientists, and Artificial Intelligence (AI) / Machine Learning (ML)
specialists.
Support the integrated interpretation of experimental and computational findings.
Requirements & Qualifications
Technical Skills & Experience
Proficiency in R (Bioconductor) and Python for advanced bioinformatics analysis.
Strong command of Linux/Unix environments and Bash scripting.
Proven track record in analyzing bulk and single-cell RNA-seq (scRNA-seq) data.
Solid experience utilizing NGS bioinformatics pipelines (covering QC, alignment, quantification, and
downstream analysis).
Deep foundational knowledge in transcriptomics, genomics, and computational biology.
Demonstrated ability to bridge the gap between experimental data and computational analysis.
Preferred Qualifications
Professional experience in the fields of stem cells, regenerative medicine, or translational research.
Familiarity with Machine Learning (ML) approaches applied to biological data.
Soft Skills
High precision and strong attention to detail.
Ability to work autonomously and manage complex datasets and projects.
Excellent organizational and problem-solving skills.
Strong communication skills and a natural aptitude for working within multidisciplinary teams.
Scientific curiosity, an innovative mindset, and a results-oriented approach.
Education & Languages
Education: Master’s Degree (M.Sc.) or Ph.D. in Bioinformatics, Computational Biology, or a closely related
discipline.
Languages: Proficiency in French and professional/scientific English (written and verbal).
Rémunération : 40 000,00€ à 45 000,00€ par an
Lieu du poste : En présentiel
