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 65+ 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.

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 (generative AI, physics‑based methods). You'll operate at the intersection of cutting‑edge algorithms, molecular simulations, and medicinal chemistry.

Responsibilities

• Computational Drug Design: Design and optimize small molecules targeting specific therapeutic areas by leveraging Aqemia's drug design engine. Systematically model ADME, toxicity, and selectivity properties.
• Communication: Present and communicate findings clearly to stakeholders across functions, ensuring data‑driven conclusions foster collaboration.
• Technology Application: Apply and validate Aqemia's baseline technologies, including generative AI algorithms and physics‑based methods, to accelerate drug discovery.
• Feedback and Improvement: Provide systematic feedback on Aqemia's platform to drive continuous improvement and enhance technological capabilities.
• Innovation and Advocacy: Proactively propose and implement new approaches to advance our Drug Discovery programs, improving accuracy, speed, and scalability.
• Interdisciplinary Collaboration: Collaborate with machine learning engineers, project managers, medicinal chemists, and physicists to push drug discovery boundaries.
• Mentoring & Technical Leadership: Mentor junior computational chemists, lead by example in rigor, reproducibility, and scientific communication, and contribute to hiring and team development.

Qualifications

• Industry Experience: At least 10 years in pharmaceutical, biotech, or CRO companies, focusing 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.
• Drug Discovery Contributions: Proven success advancing compounds from hit identification to pre‑clinical candidates.
• Diverse Target Experience: Experience with various 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 and pharmacophore hypothesis generation, virtual screening, and SAR analysis.
• QSAR and ADMET property modeling, multi‑property optimization‑based compound design, and physics‑based methods (FEP, MD, MM/GBSA).
• Familiarity with standard computational chemistry/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 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 (assessing chemical diversity, evaluating model‑generated molecules for quality/novelty, training/fine‑tuning generative architectures).
• Familiarity with co‑folding algorithms: integrating structural predictions into computational design workflows.

Please note that Aqemia currently only offers visa sponsorship for roles based in our Paris location. We will be accepting applications until 1st May. Once the role closes, our team will review all submissions and reach out to candidates selected for interview.

Why Join Us?

At AQEMIA, we work for a mission: joining us means having your own 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 like Oncology, CNS, Immuno‑inflammation, with in‑vivo proof of concept/patent‑stage programs and collaborations with top Pharma, including a $140 M Sanofi deal.

World‑Class Interdisciplinary Team: work alongside exceptional talent at the intersection of technology and life sciences, combining deep expertise in AI, physics‑based modeling, biology, and medicinal chemistry.

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: $100 M raised from leading European and International investors.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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