Principal Computational Chemist

The Role

As a Principal Computational Chemist, you'll lead the end‑to‑end design of novel small molecule therapeutics using Aqemia's computational platform, which incorporates generative AI and physics‑based methods.

Responsibilities

• Design and optimize small molecules targeting specific therapeutic areas, modeling ADME, toxicity, and selectivity properties.
• Present and communicate findings to stakeholders at all levels and across functions.
• Apply and validate Aqemia's baseline technologies, including generative AI algorithms and physics‑based methods.
• Provide systematic feedback on Aqemia's platform to drive continuous improvement and enhance technological capabilities.
• Propose and implement new approaches to advance Drug Discovery programs, improving accuracy, speed, and scalability.
• Collaborate with machine learning engineers, project managers, medicinal chemists, and physicists to push the boundaries of drug discovery.
• Mentor junior computational chemists, lead by example in rigor, reproducibility, and scientific communication, and contribute to hiring and team development.

Qualifications

• At least 10 years of experience in the pharmaceutical, biotech, or CRO industry, focused on computational chemistry for small‑molecule drug discovery.
• Deep expertise in structure‑based and ligand‑based drug design, including homology modeling, docking, SAR analysis, virtual screening, pharmacophore design, QSAR, ADMET modeling, and multi‑parameter optimization.
• Proven success in advancing compounds from hit identification to pre‑clinical candidates.
• Experience with diverse targets such as kinases, GPCRs, phosphatases, ion channels, and bromodomains.

Technical Skills

• Strong experience in structure‑based drug design and ligand‑focused techniques such as protein homology modeling, small‑molecule docking, pharmacophore hypothesis generation, virtual screening, SAR analysis.
• QSAR and ADMET property modeling, multi‑property optimization‑based compound design, physics‑based methods (FEP, MD, MM/GBSA).
• Familiarity with standard computational chemistry/chemoinformatics packages (e.g., RDKit, OpenMM, OpenFE, CCDC).
• Extensive knowledge of structural biology and solid understanding of medicinal chemistry principles.
• Ability to analyze chemical data and identify trends using statistical methods for reproducible, data‑driven decisions.
• Proficiency in Python in Linux/UNIX environments.

Nice‑to‑Have

• Prior experience with generative AI methods in drug discovery.
• Experience optimizing or evaluating generative models, including assessing chemical diversity, quality, novelty, or training/fine‑tuning generative architectures.
• Familiarity with co‑folding algorithms and integrating structural predictions into computational design workflows.

Location & Visa

Position based in Paris. Aqemia currently offers visa sponsorship only for roles located in Paris.