Senior Data Scientist - Multi-Omics AI & Target Identification

We are seeking in Toulouse (Oncopole- Langlade Location) a talented and highly motivated Senior Data Scientist - Multi-Omics AI & Target Identification with strong expertise in multi-omics analysis, machine learning, and AI for biological data to accelerate target identification, translational research, and precision medicine strategies.

As a key member of the Data Science & Biometry Department within Pierre Fabre R&D Medical Care, you will design and develop AI systems capable of learning from high-dimensional biological data (genomics, transcriptomics, proteomics, functional screens) to deepen disease understanding, uncover pathway-level mechanisms, and reveal cancer vulnerabilities across indications.

This role sits at the interface of AI research, computational biology, and drug discovery, and is embedded within the Methods & Innovation team, responsible for cross-functional initiatives involving advanced AI methodologies., * Develop and apply machine learning and deep learning models to integrate multi-omics data for target identification and prioritization.

• Contribute to biological and disease understanding by identifying molecular mechanisms, pathways, and vulnerabilities across cancer indications.
• Support diverse downstream assessments, including target discovery, toxicity prediction, and patient stratification.
• Design and train advanced models leveraging representation learning, self-supervised learning, and domain adaptation.
• Apply and adapt transformer-based architectures to biological and omics data.
• Ensure strong standards for model robustness, reproducibility, interpretability, and scientific validity.
• Work with HPC and/or cloud environments to scale model training and experimentation.
• Collaborate closely with biologists, translational scientists, and drug discovery teams to translate biological questions and hypotheses into AI-driven solutions.
• Contribute to shared AI frameworks and reusable methodological components across R&D.

• PhD or Master’s degree in Data Science, Computational Biology, or a related field.
• 5+ years of experience in data science applied to life sciences.
• Demonstrated experience in multi-omics data analysis for target discovery or translational research.
• Hands-on experience developing machine learning and deep learning models.

Technical Skills:

• Strong proficiency in Python.
• Experience with deep learning frame_works (_e.g., PyTorch).
• Solid knowledge of modern ML approaches, including transformers, representation learning, self-supervised learning, and domain adaptation.
• Familiarity with HPC and/or cloud computing environments.
• Strong grounding in bioinformatics, cancer biology, and pathway-level reasoning.

Soft Skills & Mindset

• Strong analytical and structured thinking.
• Ability to translate biological, scientific, and strategic challenges into effective AI solutions.
• Excellent cross-functional collaboration skills.
• High intellectual curiosity and innovation mindset.

Professional proficiency in English (written and oral).

We offer an attractive remuneration/benefits package: Incentives, profit-sharing, Pierre Fabre shareholding with matching contribution, health and provident insurance, 16 days of holidays (RTT) in addition to 25 days of personal holidays, public transport participation.