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 Chemist (Drug Discovery & Generative AI) who is willing to combine established industry level solutions with cutting-edge generative chemistry and AI-driven workflows for our Oncology pipeline.

As a key member of the team, the candidate will work closely with medicinal chemists and data scientists ensuring that computational hypotheses and rational lead to the selection and synthesis of promising drug candidates.

Your role within a pioneering company in full expansion:

Project Leadership & Strategy: Actively guiding and executing the computational strategy for multiple drug discovery programs simultaneously.

Integrated Molecular Modeling & Workflow Execution: Applying a hybrid approach that combines AI-driven generative workflows with physics-based simulations (MD, docking, QM, Binding Free Energy methods) to accelerate molecular design.

Property Optimization: Utilizing QSAR models and ADME-Tox predictors to evaluate chemical series, ensuring that generative chemistry outputs align with critical drug-like properties.

Infrastructure Navigation: Operating seamlessly across a hybrid technical environment, including Virtual Machines, and AWS cloud instances.

Cross-Functional Collaboration: Partnering with chemists, biologists, and ADME experts to interpret experimental results and refine computational hypotheses in real-time.

Collaborative Continuous Improvement: Partnering with team members to iteratively refine and optimize existing pipelines.

This position is based in Toulouse (Oncopole, Langlade site) compatible with teleworking up to 2 days a week according to company rules.

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, very attractive CE...

Your skills at the service of innovative projects:

Education: PhD in Computational Chemistry, Molecular Modeling, Cheminformatics, or a related field with 5+ years of industry experience.

Experience: 5+ years in a drug discovery environment with a proven track record of moving projects through the Lead Optimization phase.

Modelling: Solid experience in Structure-Based (SBDD) and Ligand-Based (LBDD) design (e.g., Molecular Dynamics, FEP, Docking).

Programming: Strong proficiency in Python for data manipulation and pipeline execution.

Infrastructure Proficiency: Ability to navigate hybrid environments (Windows VMs, Linux, and AWS).

Excellent written and oral communication skills in English

Skilled in scripting within Unix/Linux environments and using command-line interfaces with high-performance computational clusters.

Committed to good coding practices and adept at writing reproducible scripts within version control systems (e.g., Git).

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.