Senior Data Scientist - Multi-omics AI & Target Identification - CDI
Role details
Job location
Tech stack
Job description
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. Your role within a pioneering company in full expansion, * Develop and apply machine learning and deep learning models to integrate multi-omics data for target identification and prioritization.
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Contribute to biological and disease understanding by identifying molecular mechanisms, pathways, and vulnerabilities across cancer indications.
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Support diverse downstream assessments, including target discovery, toxicity prediction, and patient stratification.
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Design and train advanced models leveraging representation learning, self-supervised learning, and domain adaptation.
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Apply and adapt transformer-based architectures to biological and omics data.
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Ensure strong standards for model robustness, reproducibility, interpretability, and scientific validity.
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Work with HPC and/or cloud environments to scale model training and experimentation.
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Collaborate closely with biologists, translational scientists, and drug discovery teams to translate biological questions and hypotheses into AI-driven solutions.
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Contribute to shared AI frameworks and reusable methodological components across R&D.
Requirements
- 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 frameworks (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).
Benefits & conditions
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. Who you are ? Your skills at the service of innovative projects
