Mots-Clés
mRNA Vaccine
Multi-OMICS
Machine Learning
Immunology
Description
Context and Project Summary
Our laboratory RESPIVIR is hiring a talented and motivated Research Engineer to join the ambitious mRESPIVAC project in the framework of the EU Health IPCEI “Med4Cure” initiative. The CIRI is a world-class research institute affiliated with INSERM, CNRS, ENS Lyon, and Lyon 1 University, bringing together 400 scientists with diverse expertise. We offer a dynamic, collaborative, and stimulating scientific environment with direct access to state-of-the-art technological platforms.
The mRESPIVAC project, carried out in partnership with the Gimap team (CIRI, Saint-Etienne), aims to establish a unique translational clinical research center to accelerate the evaluation and development of next- generation mRNA vaccines against respiratory viruses. In response to the lessons from the COVID-19 pandemic, this project will create a “bench-to-bedside” pipeline to improve vaccine efficacy, particularly in generating durable mucosal immunity. By combining innovative preclinical models (in vitro 3D ALI cultures and organoids, in vivo models) with advanced Omics technologies and artificial intelligence, mRESPIVAC will develop new methods for the early prediction of vaccine immunogenicity and reactogenicity. This project is a strategic asset for the French and European vaccine ecosystem, contributing to our sovereignty and responsiveness to future pandemics.
The successful candidate will be at the heart of the project’s bioinformatics and data science efforts, playing a critical role in transforming massive, multi-modal biological data into actionable insights for vaccine development.
Role Summary
As a Research Engineer, you will be responsible for the design, implementation, and execution of bioinformatics analysis pipelines for large-scale Omics datasets (transcriptomics, proteomics, etc.) generated within the project. You will work in a multidisciplinary team of virologists, immunologists, and clinicians to integrate and analyze data from preclinical models and human clinical samples. Your primary objective will be to identify novel biomarkers and contribute to the development of machine learning models that can predict the efficacy and safety of mRNA vaccine candidates. This is a unique opportunity to contribute to a high-impact project at the forefront of vaccine research.
Missions and Key Responsibilities
Your main missions will be to:
- Design and Implement Analysis Pipelines: Develop, optimize, and maintain robust and scalable pipelines for the pre-processing, quality control, and analysis of various NGS datasets (bulk, single-cell, and spatial transcriptomics; VDJ-seq; IgA-Seq).
- Integrative Multi-Omics Analysis: Apply advanced statistical methods to integrate and analyze heterogeneous datasets from in vitro 3D organotypic models and in vivo animal studies to understand vaccine-induced immune responses.
- Biomarker Discovery: Perform differential analysis and pathway enrichment to identify and validate molecular biomarkers predictive of vaccine immunogenicity, reactogenicity, and protection.
- Develop Predictive Models: Collaborate on the construction, training, and validation of machine learning algorithms to create predictive scores for ranking vaccine candidates based on their safety and efficacy profiles.
- Ensure Reproducibility and Scalability: Deploy analysis workflows on an HPC infrastructure using reproducible software environments (Conda, Docker/Apptainer) and standardized data management practices.
- Scientific Collaboration and Support: Work closely with experimental biologists and clinicians to contribute to experimental design, interpret complex biological results, and present findings to a multidisciplinary audience.
Required Profile
Education and Experience:
- Master’s degree or Engineering degree (Bac+5) in Bioinformatics, Computational Biology, Data Science, or a related discipline.
- At least 3 years of experience in the field.
Essential Know-How and Knowledge:
- Scientific Programming: Strong proficiency in R and/or Python.
- Statistical Analysis: Solid experience in hypothesis testing, multiple test correction, linear models, and other statistical methods applied to biological data.
- Bioinformatics & NGS: In-depth knowledge of NGS technologies, experimental design, pre-processing workflows, and bioinformatics algorithms. Familiarity with public bioinformatics databases (e.g., Ensembl, GEO, SRA).
- HPC & Reproducibility: Proven experience using academic HPC infrastructure and tools for creating reproducible environments like Conda and Docker/Apptainer.
- Machine Learning: Practical experience in applying machine learning techniques to biological data.
- Multi-Omics Integration: Demonstrated ability to perform integrative analysis of different Omics data types.
- Biology: Fundamental knowledge of biology, virology, and immunology is essential for interpreting data in the context of the project.
Personal Skills:
- Excellent problem-solving skills and the ability to work autonomously
- Strong organizational skills and the capacity to manage multiple tasks simultaneously.
- A collaborative and professional approach, with excellent communication skills.
- Curiosity, proactivity, and a strong interest in translational research and public health.
- Fluency in written and spoken French and English.
How to Apply
Interested candidates are invited to send their application with the subject “mRESPIVAC application” to: manuel.rosa-calatrava@univ-lyon1.fr and clement.droillard@univ-lyon1.fr.
Please include the following documents in a single PDF file:
- A detailed Curriculum Vitae (CV) including a list of any publications or projects.
- A Cover Letter explaining your motivation and suitability for the position.
- Contact information for 1-2 professional references.
Deadline for application: December 1st, 2025