Research Engineer

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