Pierre Fabre is the 2nd largest dermo-cosmetics laboratory in the world, the 2nd largest private French pharmaceutical group and the market leader in France for products sold over the counter in pharmacies.

Its portfolio includes several medical franchises and international brands including Pierre Fabre Oncologie, Pierre Fabre Dermatologie, Eau Thermale Avène, Klorane, Ducray, René Furterer, A-Derma, Naturactive, Pierre Fabre Oral Care. 

Established in the Occitanie region since its creation, and manufacturing over 95% of its products in France, the Group employs some 10,000 people worldwide. Its products are distributed in about 130 countries. 86% of the Pierre Fabre Group is held by the Pierre Fabre Foundation, a government-recognized public-interest foundation, while a smaller share is owned by its employees via an employee stock ownership plan. 

In 2019, Ecocert Environment assessed the Group’s corporate social and environmental responsibility approach in accordance with the ISO 26000 sustainable development standard and awarded it the “Excellence” level.

Pierre Fabre is recognized as one of the "World's Best Employers 2021" by Forbes. Our group is ranked in the Top 3 in the cosmetics industry and in the Top 10 in the pharmaceutical industry worldwide. 

Your mission

We are seeking a talented and highly motivated Senior Computational Biologist - Multi-omics for Target Discovery and Validation with strong expertise in multi-omics analysis applied to target discovery and validation. You will work at the interface between the Data Science & Biometry and the Drug Discovery Departments, collaborating daily with biologists to drive the discovery and validation of therapeutic targets.

You will be a key member of the Data Science & Biometry Department within Pierre Fabre R&D Medical Care. You will be responsible for exploring, mining and integrating proprietary and public high-dimensional biological data (genomics, transcriptomics, proteomics, functional screens) to test and validate cancer vulnerabilities across indications.

The role sits within the Target & Drug Discovery Data Science team. You will contribute to and be responsible for discovery portfolio projects, and you collaborate on them together with the other Data Science teams, including the Computational Chemistry, Biomarker Development and the Methods & Innovation team.

Your role within a pioneering company in full expansion:

Key Responsibilities

• Contribute to biological and disease understanding by identifying molecular mechanisms, pathways, and vulnerabilities across cancer indications and immuno-dermatology.
• Process, analyze, and interpret molecular datasets from clinical studies, including genomics, bulk and single-cell transcriptomics, spatial transcriptomics, proteomics, and epigenomics.
• Apply machine learning and deep learning models to integrate multi‑omics data for target identification and prioritization.
• Contribute to and be responsible for discovery portfolio projects, aligning priorities and activities with the drug discovery collaborators.
• Contribute to the team target ID and validation strategies, and stay up-to-date with the relevant literature and data landscape.
• Work with HPC and/or cloud environments to scale up large data mining and analyses campaigns.
• Work according to industry standards good-coding practices and reproducible research.
• Thrive in a collaborative, inclusive team culture built on trust, creativity, openness, and scientific curiosity where your ideas are valued and your voice matters.

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...

Your skills at the service of innovative projects:

Key Qualifications

• PhD or Master’s degree in Bioinformatics, Computational Biology, Data Science, or a related field.

• 5+ years of experience in computational biology applied to target discovery and validation.
• Solid understanding of cancer biology and the molecular mechanism of cancer vulnerabilities.
• Demonstrated experience in multi‑omics data analysis for target discovery and validation.
• Strong proficiency in R and Python.
• Familiarity with HPC and/or cloud computing environments.
• Familiarity with FAIR data principles and reproducible research.
• Demonstrated ability to thrive in cross functional, matrixed project teams, contributing effectively to multidisciplinary research.
• Strong communication, organizational, and interpersonal skills, including the ability to collaborate, present results clearly, and engage with diverse scientific partners.
• Genuine passion for applying computational biology for improving human health through drug discovery.
• Professional proficiency in English (written and oral).

Preferred Qualifications

• Experience in applying machine learning and deep learning models to integrate multi‑omics data for target identification and prioritization.
• Familiarity with nextflow (nf-core) pipelines for multi-omics data preprocessing.
• Familiarity with TileDB data infrastructure.
• Familiarity with applying agentic-AI workflows to computational biology.
• Strong publication record or external visibility in scientific communities.

We are convinced that diversity is a source of fulfillment, social balance and complementarity for our employees, which is why our offers are open to all, without restriction.