Research Engineer - Bioinformatics

SFBI; Toulouse; On-site; EUR 45,000 - 70,000; Full time

Job summary

INFINITy in Toulouse seeks a Research Engineer in bioinformatics to support single-cell and spatial omics projects investigating immune regulation of mammary gland physiology. You will collaborate with experimental scientists to design analyses and build reproducible workflows.

Responsibilities include QC, data processing, visualization, pipeline development, data submission and training colleagues in relevant methods. A strong background in computational biology is essential.

Qualifications

• Proficiency in R and/or Python and analysis of scRNA-seq and spatial transcriptomics.
• Knowledge of transcriptomic data processing, dimensionality reduction and clustering.
• Basic knowledge of immunology, physiology and molecular biology.
• Clear, organized and documented coding practices; strong communication.

Responsibilities

• Define bioinformatics requirements with researchers and project objectives.
• Analyse scRNA-seq and spatial datasets including QC, normalisation, clustering and differential expression.
• Develop reproducible analysis pipelines for multi-sample datasets.
• Integrate multi-modal data, reanalyse existing datasets and support future studies.
• Develop scripts and tools; generate figures, reports and presentations.
• Prepare public data submissions (e.g., GEO) and train team members.

Skills

R

Python

scRNA-seq

Spatial transcriptomics

Seurat/Scanpy

Education

Master’s degree or PhD in bioinformatics or computational biology

Tools

Seurat

Scanpy

GEO

QuPath

Job description

Bioinformatics Single-cell transcriptomics Spatial transcriptomics scRNA-seq Omics data analysis R Python Seurat Scanpy Image analysis Histology Machine learning Immunology Computational biology

Description

A research engineer position (IE/IR) in bioinformatics is available in the laboratory of Dr Dan Corral at INFINITy (Toulouse, France) to support research projects investigating the immune regulation of mammary gland physiology and how environmental factors influence these interactions using single-cell and spatial omics approaches.

Research Environment

INFINITy (Toulouse Institute for Infectious and Inflammatory Diseases) is a joint research institute affiliated with CNRS, INSERM and Université Toulouse III, dedicated to immunology, infectious diseases and inflammation. Located in Toulouse, France, the institute brings together 18 internationally recognized research teams, supported by four state-of-the-art technological platforms and dedicated support services.

The successful candidate will work closely with experimental scientists, contributing to the design, analysis and interpretation of transcriptomic datasets across several research projects in a collaborative and stimulating scientific environment.

Main Responsibilities

• Work with researchers to understand project objectives and define bioinformatics requirements.
• Analyse scRNA-seq and spatial transcriptomics datasets, including quality control, normalisation, clustering, annotation and differential expression.
• Develop and standardise reproducible analysis pipelines and workflows for systematic processing of datasets.
• Integrate multi-sample, multi-modal and multi-source biological datasets; reanalyse existing datasets and support future studies.
• Develop well-documented scripts and analysis tools; generate clear figures, reports and presentations.
• Prepare and manage public data submissions (e.g., GEO); train team members in relevant methods and maintain awareness of new approaches.

Candidate Profile

Applicants should hold a Master’s degree or PhD in bioinformatics, computational biology, or a related field, with experience in analysing high-throughput biological data.

Essential Qualifications

• Proficiency in R and/or Python and experience with scRNA-seq and spatial transcriptomics analysis tools (e.g., Seurat, Scanpy or equivalent).
• Knowledge of transcriptomic data processing, omics databases, dimensionality reduction and clustering (PCA, nearestneighbour graphs, t-SNE/UMAP, hierarchical clustering).
• Basic knowledge of immunology, physiology and molecular biology.
• Clear, organised and documented coding practices; strong communication and collaborative skills.

Desirable Qualifications

• Experience with histological and fluorescence image analysis (e.g., QuPath, Fiji/ImageJ, CellProfiler), including machine learning-based approaches.
• Familiarity with GEO submissions, workflow automation and version control.
• Experience training colleagues and explaining computational results to non-specialists.

Anticipated start date: Early 2027