Head of Molecular Generation & AI Design
About AQEMIA
About AQEMIAAQEMIA 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.For more information, visit AQEMIA.com and our LinkedIn.About Our TeamAQEMIA 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 roleAs Manager of Molecular Generation Team, you will lead the multidisciplinary team responsible for developing our methods to design novel, highly potent and synthesizable molecules. You will be responsible for leveraging physics-based methods and state-of-the-art Machine Learning techniques to guide molecular design, focusing specifically on 3D structural constraints and target interactions.What You’ll Do
- Strategic & Technical Leadership:
- Define and execute the roadmap for developing structure-based AI generative models
- Establish clear, measurable KPIs for synthesis success and novelty of generated molecules
- Drive the integration of physics-based calculations into the Generative Machine Learning workflow to enhance the chemical realism and relevance of generated molecules
- People & Team Management:
- Hire, manage and mentor a highly skilled team of 6+ scientists, encompassing AI Research Scientists and Computational Chemists
- Own the recruitment process for key technical hires, ensuring the team maintains world-class expertise at the intersection of chemistry, physics and AI
- Foster a culture of high performance, psychological safety and continuous learning, providing technical guidance and growth opportunities for individual contributors
- Collaboration & Delivery:
- Ensure seamless handoff of molecular generation algorithm to downstream teams
- Enable integration of physics and AI-based predictors in the molecular generation workflow
- Communicate complex scientific progress and strategic risks clearly
- Master degree or PhD in Machine Learning, Computational Chemistry, Statistical Mechanics, Physics, Computer Science or a related field
- Minimum of 2+ years of experience leading a machine learning team, computational R&D team in Drug Discovery or a closely related field
- Proven expertise in Generative AI techniques
- Proficiency in Python, experience with MLOps and cloud computing environments
- Ability to translate fundamental scientific research into a clear, scalable product roadmap that aligns with commercial goals
- Exceptional ability to communicate complex concepts to both specialized scientists and non-technical stakeholders
- Proven ability to manage risk, handle scientific failure inherent in R&D, and lead an autonomous team in a fast-paced startup environment
- Pragmatic and Impact-Driven - Focused on delivering solutions that work in real-world applications, balancing scientific rigor with practical usability
- Eagerness to Learn - A strong curiosity for scientific advancements and a willingness to continuously expand your expertise
- Love for High Scientific Challenges - Enthusiasm for tackling complex problems at the frontier of AI and drug discovery
- Team-Oriented - A collaborative spirit, thriving in an interdisciplinary environment
- Humility - Open to feedback and different perspectives, always striving for improvement