Senior Computational Chemist, Platform Development- F/M

We are seeking a Senior Computational Chemist, Platform Development, to join the Computational & Generative Chemistry team at Laboratoires Pierre Fabre, which supports small-molecule discovery across the portfolio. We combine physics-based methods with AI/ML and are building an AWS platform to make reliable, reproducible computational tools accessible to project teams. Your role within a pioneering company in full expansion: As Senior Computational Chemist, Platform Development, you will select, build, benchmark and deploy computational chemistry workflows. You will pilot them with discovery teams to validate scientific performance and usability, then enable computational chemists working on drug discovery projects and other portfolio team members to run them independently. Our methods span:
· AI-driven generative chemistry and molecular design
· Molecular preparation, docking and AI-enabled virtual screening, including large libraries
· Structure-based deep learning
· Pharmacophore and shape-based modelling
· Machine-learning prediction of molecular properties and ADME/Tox
· Molecular dynamics and binding free-energy calculations
· QM-based conformational analysis and scoring

What you'll do
· Evaluate open-source and commercial tools, and recommend build-versus-buy options with licensing and cost in mind.
· Develop modular, reproducible workflows from molecule generation through prioritisation.
· Deploy containerised pipelines on AWS CPU and GPU infrastructure, scaling workloads while managing cost.
· Partner with IT and cloud engineering on infrastructure, data, security, access and software licensing.
· Benchmark and monitor workflows for scientific performance, throughput and cost; communicate results and improve the platform over time.
· Pilot workflows with discovery teams, incorporate their feedback and prepare validated pipelines for routine project use.
· Create documentation and hands-on training so project teams can operate pipelines independently; provide ongoing support and mentor colleagues.

What we offer
· A high-ownership role shaping computational capabilities for drug discovery.
· Enable discovery projects from hit finding to lead optimisation with validated, scalable computational workflows.
· Access to cloud computing and a choice of open-source and commercial tools.
· Close collaboration with a multidisciplinary team across computational chemistry, medicinal chemistry, biology and DMPK. This position is 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... Your skills at the service of innovative projects:
• PhD in computational chemistry, chemoinformatics, molecular modelling or a related field, with 5+ years in drug discovery; or an MSc with 8+ years of equivalent experience.
• Hands-on expertise in several computational chemistry methods, such as docking, virtual screening, molecular dynamics, free-energy calculations or ADME prediction.
• Practical experience with generative chemistry or ML for molecular design or property prediction.
• A track record of building and maintaining production workflows used by others.
• Strong Python skills and experience with scientific tools such as RDKit, NumPy and pandas.
• Experience running workloads on AWS or HPC, using job schedulers and containers.
• Working knowledge of Linux, Git, testing and software engineering practices.
• Clear communication skills and an interest in partnering with and teaching computational and medicinal chemists.
• Fluent English. Also useful: Experience with infrastructure-as-code, workflow managers, Kubernetes, ultra-large library screening, cloud-based commercial software, GPU computing, web dashboards. French, or willingness to learn, is a plus.