Bioinformatics Engineer - Multi-Omics Cancer Analytics

SFBI; Créteil; Sur place; EUR 45 000 - 65 000; Plein temps

Résumé du poste

IMRB's MINT-Hep team in Créteil, INSERM U955, is seeking a highly motivated Research Engineer in Bioinformatics to conduct multi-omics, single-nucleus RNA-seq and spatial transcriptomic analyses in liver cancer.

The successful candidate will test, deploy and maintain computational tools, develop reproducible pipelines, and collaborate with biologists and clinicians to translate biological questions into computational analyses.

Qualifications

• Training in bioinformatics with a biology focus or cancer research.
• Experience working in a Unix/Linux environment.
• Good knowledge of R and statistical data analysis.
• Experience with genomic and/or transcriptomic data analysis.
• A background in cancer genomics, tumor biology or immuno-oncology is a plus.
• Ability to work collaboratively across disciplines.

Responsabilités

• Test, improve and deploy computational tools for genomic and transcriptomic analyses.
• Develop and maintain reproducible pipelines for bulk RNA-seq, WES/WGS, single-nucleus RNA-seq and spatial transcriptomics.
• Perform end-to-end data analysis: QC, preprocessing, normalization, statistics and visualization.
• Develop approaches for multi-omic and spatial data integration.
• Maintain and document analysis pipelines and code.
• Collaborate with biologists, pathologists and clinicians to translate questions into analyses.

Connaissances

Unix/Linux

R and statistics

Multi-omics data integration

Collaborative mindset

Formation

Bioinformatics training

Outils

R

Description du poste

IMRB's MINT-Hep team in Créteil, INSERM U955, is seeking a highly motivated Research Engineer in Bioinformatics to conduct multi-omics, single-nucleus RNA-seq and spatial transcriptomic analyses in liver cancer.

The successful candidate will test, deploy and maintain computational tools, develop reproducible pipelines, and collaborate with biologists and clinicians to translate biological questions into computational analyses.