Computational Chemist - Generative Chemistry

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. 

The location of the position will be Toulouse (Oncopole, 31) or Boulogne (92) with high flexibility in terms of commuting from France/Europe and home office.

We are seeking a talented and highly motivated Computational Chemist, specializing in Generative Chemistry, to join our growing Data Science and Biometry group.

The ideal candidate will leverage advanced AI-driven generative chemistry techniques to support hit identification, hit to lead and lead optimization phases of drug discovery, driving our growing portfolio. The successful candidate will work closely with chemists, biochemists, and structural biologists to pioneer and build our computational chemistry activities towards the design of novel drug candidates.

The Pierre Fabre Group is dedicated to Medical Care R&D, aiming to provide innovative treatments for patients. Oncology is a major priority and constitutes a strategic focus for the Pierre Fabre Group.

Our internal R&D pipeline, supplemented with future external opportunities, will be central in shaping the future orientation of Pierre Fabre Medical Care.

Your responsibilities include, but are not limited to:

• Collaborate with drug discovery teams to identify and recommend opportunities for applying generative chemistry to accelerate processes and increase the probability of success (PoS) of our molecules.
• Develop and deploy AI-driven models for molecular generation, docking, and stable conformers to support drug discovery and development.
• Identify and evaluate external partnering opportunities to align with our strategic priorities.
• Stay updated on the latest developments in generative chemistry and their applications in life sciences to ensure our team remains at the forefront of technology.
• Work alongside chemists, biochemists, and structural biologists to integrate generative chemistry into the drug design process.

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...

Who are you?

• Advanced degree (MSc or PhD) in Chemistry, Biochemistry, Chemical Engineering, Data Science, or a related field.
• 5+ years of experience in drug discovery, with good knowledge in structure-based drug design (e.g. molecular docking, conformational analysis, molecular dynamics), ligand-based drug design and AI-driven approaches (e.g. ML model, generative chemistry).
• Strong understanding of AI-driven generative models, computational chemistry frameworks, architectures, limitations, and pitfalls.
• Experienced with cloud computing platforms such as Azure, AWS, or Google Cloud for deploying computational models.
• Experienced in developing pipelines using open-source tools.
• Proficient in programming languages such as Python and R, with a proven track record of presenting scientific results through static and interactive reports and visualizations (e.g., RShiny).
• 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).
• Demonstrated experience with Maestro and Makya is a plus.
• Excellent written and oral communication skills in English, with the ability to convey complex information to both technical and non-technical stakeholders.

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.