Principal Computational Chemist

About AQEMIA

AQEMIA is a drug invention company dedicated to creating entirely new medicines to address major unmet medical needs. At the core of our mission is QEMI , our proprietary molecule-invention platform, which uniquely combines cutting‑edge science with advanced technology. Powered by physics‑based modeling, statistical mechanics, and generative AI, QEMI allows our teams to design novel drug candidates from first principles.

What makes AQEMIA different is our commitment to true innovation: our research is dedicated to the invention of new molecular entities, not the refinement of existing ones. We focus on inventing never‑before‑seen molecules, without relying on experimental data, and advancing them into a growing pipeline of proprietary programs and strategic partnerships with leading pharmaceutical companies.

Our most advanced preclinical programs are currently in vivo optimization, targeting diseases still waiting for effective treatments, offering our teams the opportunity to work on science that can make a real difference in people’s lives.

About Our Team

AQEMIA brings together a diverse, multidisciplinary team of over 80 professionals based in Paris and London. Our scientists and engineers, including chemists, physicists, machine learning experts, and software engineers, work side by side to push the boundaries of early‑stage drug discovery. This close collaboration across disciplines is central to our approach, enabling us to tackle complex scientific challenges from first principles and translate cutting‑edge ideas into novel therapeutic candidates.

At AQEMIA, team members are encouraged to contribute their expertise, learn from one another, and play an active role in shaping the future of drug invention.

Responsibilities

• Design and optimize small molecules targeting specific therapeutic areas by leveraging AQEMIA's drug design engine. Systematically model ADME, toxicity, and selectivity properties.
• Communicate findings clearly to stakeholders at all levels and across functions. Ensure conclusions are robust and data‑driven, fostering trust and collaboration within the team.
• Apply and validate AQEMIA's baseline technologies, including generative AI algorithms and physics‑based methods, to accelerate drug discovery.
• Provide systematic feedback on AQEMIA's platform to drive continuous improvement and enhance technological capabilities.
• Proactively 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 boundaries of drug discovery.
• Mentor junior computational chemists on project execution and methodology. Lead by example in rigor, reproducibility, and scientific communication. Contribute to hiring and team development for the computational chemistry team.

Qualifications

• At least 10 years of experience in pharmaceutical, biotech, or CRO companies, focused on computational chemistry for small molecule drug discovery.
• Deep expertise in structure‑based and ligand‑based drug design: homology modeling, docking, SAR analysis, virtual screening, pharmacophore design, QSAR, ADMET property modeling, multi‑parameter optimization.
• Proven success in advancing compounds from hit identification to pre‑clinical candidates.
• Experience with diverse targets, including 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, and SAR analysis.
• Experience with QSAR and ADMET property modeling, multi‑property optimization‑based compound design, and physics‑based methods (FEP, MD, MM/GBSA).
• Familiarity with standard computational chemistry and cheminformatics packages (e.g., RDKit, OpenMM, OpenFE, CCDC).
• Extensive knowledge of structural biology.
• Solid understanding of medicinal chemistry principles and computational methods for optimizing drug properties.
• Ability to analyze chemical data and identify trends using statistical methods to ensure reproducibility and data‑driven decision‑making.
• 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 (assessing chemical diversity, evaluating model‑generated molecules for quality/novelty, training/fine‑tuning generative architectures).
• Familiarity with co‑folding algorithms: experience integrating structural predictions into computational design workflows.

Why Join Us?

At AQEMIA, we work for a mission: joining us means having an impact on changing the way drugs are discovered, and helping to shape the direction of our fast‑growing company and team.

Expanding Drug Discovery Pipeline : focused on critical therapeutic areas such as Oncology, CNS, Immuno‑inflammation, with in vivo proof of concept and patent‑stage programs. Collaborations with top Pharma, including a $140M Sanofi deal.

World‑Class Interdisciplinary Team : work alongside exceptional talent at the intersection of technology and life sciences. Our teams combine deep expertise in AI, physics‑based modeling, biology, and medicinal chemistry to push the boundaries of innovation.

DeepTech Recognition : AQEMIA is proud to be part of the French Tech 120 and France 2030, highlighting our role as a key player in Europe’s DeepTech ecosystem.

Prime Location with Flexibility : our offices are located in the heart of Paris and London (King’s Cross), with flexible work arrangements including up to two remote days per week.

Strong Financial Backing : $100M raised from leading European and international investors.