Senior Multi-Omics AI Scientist for Target Discovery

INSTITUT DE RECHERCHE PIERRE FABRE SAS; Pechbusque; Hybrid; EUR 90,000 - 130,000; Full time

Benefits offered by this job

Incentives

Profit-sharing

Employee stock ownership

Health and provident insurance

16 RTT

25 days personal holidays

Public transport participation

Job summary

Pierre Fabre Laboratories is seeking a Senior Data Scientist for Multi-Omics AI & Target Identification in Toulouse. The role focuses on integrating high‑dimensional data (genomics, transcriptomics, proteomics) to identify targets and inform translational research and precision medicine strategies.

You will design AI systems that learn from omics data, collaborate with biology and drug discovery teams, and scale training in HPC/cloud environments. English communication is essential.

Qualifications

• PhD or Master’s in Data Science, Computational Biology, or related field.
• 5+ years of data science experience in life sciences with multi-omics analysis.
• Hands-on experience with ML/DL models.

Responsibilities

• Develop and apply ML/DL models to integrate multi-omics data for target identification.
• Identify molecular mechanisms, pathways, and vulnerabilities across cancer indications.
• Support downstream assessments including target discovery, toxicity prediction, and patient stratification.
• Design and train advanced models using representation learning and domain adaptation.
• Apply transformer-based architectures to biological/omics data.
• Ensure robust, reproducible, interpretable modeling practices.

Skills

Python

PyTorch

Transformers

Representation learning

Self-supervised learning

Domain adaptation

HPC/Cloud

Bioinformatics

Cancer biology

Pathway-level reasoning

English communication

Education

PhD or Master’s degree in Data Science, Computational Biology, or related field

Job description

Pierre Fabre Laboratories is seeking a Senior Data Scientist for Multi-Omics AI & Target Identification in Toulouse. The role focuses on integrating high‑dimensional data (genomics, transcriptomics, proteomics) to identify targets and inform translational research and precision medicine strategies.

You will design AI systems that learn from omics data, collaborate with biology and drug discovery teams, and scale training in HPC/cloud environments. English communication is essential.