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About the Role
Design molecules that advance drug discovery programs from hit identification through lead optimization to pre-clinical candidate nomination. Combine physics-based modeling, generative AI, and medicinal chemistry insights to guide molecule selection for internal programs and pharma partnerships. Develop and test new methods, influencing the next generation of AI and platform capabilities, including AI agents and autonomous computational workflows. Own key design decisions and become a scientific leader within the drug discovery team.
Responsibilities
- Design, prioritize, and optimize small molecules across multiple programs to drive compounds from hit identification through lead optimization to candidate nomination.
- Own the design hypothesis: set clear, testable hypotheses, separate knowns from beliefs, and adapt quickly based on evidence.
- Apply the full computational toolkit, including structure- and ligand-based design, docking, molecular dynamics, free energy calculations, chemoinformatics, and generative AI.
- Integrate biochemical, biophysical, pharmacological, and ADME-Tox data with predictions to identify trends, risks, and opportunities, providing clear recommendations for next steps.
- Pilot new technology in live projects: test AQEMIA’s generative and predictive models, AI agents, and automated workflows, benchmark them, and provide feedback to platform and ML teams.
- Collaborate daily with medicinal chemists, biologists, ML scientists, physicists, and project managers on internal programs, pharma collaborations, and early-stage pre-program work.
- Communicate findings, recommendations, and risks clearly and directly in project reviews and strategy discussions, flagging changes to the plan based on results.
Requirements
- PhD in computational chemistry, medicinal chemistry, chemical biology, biophysics, or a related discipline, or a Master’s in a relevant field with equivalent industry experience.
- 3+ years of industry experience (pharma, biotech, or CRO) in small molecule drug discovery, working in integrated project teams with medicinal chemists and biologists.
- Hands-on contribution to programs across hit identification, hit-to-lead, and lead optimization as a core design contributor.
- Strong expertise in structure-based and ligand-based drug design, protein-ligand interactions, and medicinal chemistry principles.
- Practical experience with docking, molecular dynamics, free energy methods, and chemoinformatics, using tools such as RDKit, OpenMM, AmberTools, GROMACS, or equivalent.
- Working proficiency in Python and Linux, comfortable running, reading, and adapting scripts and computational workflows.
- A direct, evidence-driven communicator who is clear about knowledge, uncertainties, and proposed actions.
Skills
- Physics-based modeling
- Generative AI
- Medicinal chemistry
- Structure-based drug design
- Ligand-based drug design
- Protein-ligand interactions
- Docking
- Molecular dynamics
- Free energy methods
- Chemoinformatics
- Python
- Linux
- AI agents for molecular design
- Autonomous computational workflows
- Multi-parameter optimization
- ADME-Tox prediction
Location
- Paris
- London
Work Type
- Hybrid
- Remote (up to two days per week)
Experience Level
- 3+ years of industry experience
Education Level
- PhD in computational chemistry, medicinal chemistry, chemical biology, biophysics, or related discipline
- Master's degree in a relevant field with equivalent depth of industry experience
Benefits
- Flexible work arrangements
About the Company
- AQEMIA is a drug invention company focused on creating new medicines for unmet medical needs using its proprietary QEMI platform, which combines physics-based modeling, statistical mechanics, and generative AI.
- The company focuses on inventing novel molecular entities rather than refining existing ones, advancing them into proprietary programs and partnerships.
- AQEMIA has a diverse, multidisciplinary team of over 80 professionals in Paris and London, including chemists, physicists, machine learning experts, and software engineers.
- The Drug Discovery Sciences team integrates medicinal chemistry, computational chemistry, biology, and translational science, working at the intersection of AI-driven drug design, molecular simulations, and experimental science.
- AQEMIA is recognized as a key player in Europe's DeepTech ecosystem, being part of the French Tech 40 and France 2030.
- The company has raised $100M from leading investors and has a $140M Sanofi deal.
Equal Opportunity
- We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. 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.