Principal Computational Chemist
Aqemia
About Aqemia
Aqemia is a next-generation pharmatech reinventing drug discovery with quantum-inspired physics and generative AI.
Our mission: design innovative small-molecule drug candidates for dozens of critical diseases, faster and smarter, without relying on experimental data.
Unlike traditional approaches, Aqemia starts drug discovery purely in silico. By combining physics-based models with large language models trained on proprietary data, we identify promising molecules with high accuracy before synthesis.
We’ve already delivered multiple preclinical successes and secured strategic partnership. Our internal pipeline is growing fast, with several programs in in vivo optimization.
We’re a team of 65+ based in Paris and London, we bring together chemists, physicists, engineers, and machine learning experts to push the boundaries of what’s possible in early-stage drug discovery.
About the team you’ll join
As a Principal Computational Chemist, you will join Aqemia’s Drug Discovery Platform Teams and lead efforts to develop cutting-edge computational chemistry pipeline to scale and accelerate drug discovery. You will collaborate closely with computational chemists, AI researchers and drug discovery experts to integrate your innovations into Aqemia’s platform, ensuring direct impact on the discovery of novel therapeutics.
About the Role
We are seeking a Principal Computational Chemist, the most senior individual contributor rank at Aqemia. This role is designed for a scientist at the state of the art of their field, with deep expertise and a strong track record of impactful contributions. The Principal Computational Chemist will oversee complex scientific projects, mentor scientists, and actively shape our scientific roadmap.
This means you will:
Be a Technical Leader - Drive the development of cutting-edge computational chemistry methodologies for molecular modeling and drug discovery.
Mentor and Support the Team - Act as a scientific and technical mentor to junior and mid-level researchers, fostering innovation and knowledge-sharing within the team.
Bridge Research and Application - Work closely with interdisciplinary teams (computational chemistry, AI and drug discovery experts) to translate computational chemistry research into real-world impact.
Your Role
Lead research initiatives to develop and apply novel computational chemistry methods to virtual screening, hit optimisation and lead optimisation.
Design and implement advanced computational chemistry techniques , including protein ligand complex generation.
Collaborate with interdisciplinary teams , including computational chemists, AI Research scientists, physicists, data scientists and medicinal chemists.
Mentor and guide junior researchers and engineers , fostering a culture of scientific innovation and excellence.
Polite note: this position does not involve manual compound design in Drug Discovery Programs.
Your Profile
- Strong problem-solving skills, autonomy and a collaborative mindset.
- PhD in Computational Chemistry, Biophysics, Statistical Mechanics, or a related field.
- Extensive experience (10+ years) in computational chemistry and drug discovery including 5 years in the drug discovery industry .
- Recognised expertise in molecular modeling, complex generation, protein-ligand interactions, free energy calculations, virtual screening, ADME properties and related areas.
- Strong knowledge of uncertainty quantification and its application in molecular design.
- Proven ability to deliver impactful scientific contributions at the forefront of the field.
- Experience mentoring and guiding scientists in a collaborative, high-performance environment.
- Proficiency in programming (e.g., Python) and experience with industry-standard computational chemistry tools.
Preferred Mindset
At Aqemia, we believe that great science thrives in the right mindset and culture. We are looking for candidates who embody the following principles:
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.
Aqemia’s Recruitment team leads all recruitment activities for the company. We will not recognise any notional ownership recruitment companies claim over candidates presented directly to hiring managers without our Recruitment team's consent. Unsolicited resumes sent to us from recruiters do not constitute any type of relationship between the recruiter and Aqemia, and we will not be obligated to pay fees should we hire from those resumes.
Why Join Us
At Aqemia, engineers don’t just build software, they help discover real drugs.You ’ll work at the intersection of AI, physics and chemistry, transforming bold scientific ideas into robust, production-grade tools that accelerate discovery.
DeepTech Mission : Build the platform that powers AI-driven drug discovery, combining quantum-inspired physics with generative models
Real-World Impact : Every feature shipped helps scientists prioritize molecules and design better candidates, faster
Modern Stack & Challenges : Python, FastAPI, Airflow, Snowflake, Kubernetes, ML workflows, scientific infra, data engineering at scale
High Ownership, High Impact : Engineers contribute to architecture, tooling, and scientific decision-making
Interdisciplinary Team : Collaborate with chemists, physicists, ML researchers, and product teams
Prime Locations : Central Paris or London offices, with 2 remote days/week
Strategic Traction : Backed by $100M in funding and a $140M partnership with Sanofi
Join us if you’re excited to shape the future of AI-driven drug discovery, and want your code to change the course of real diseases.
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