Applied AI Research Scientist
Aqemia ParisEst. Est. EUR 55,000–80,000 / yearMid
Estimated range based on role, country and industry — not published by the company.
Key requirements
- Python
- Machine Learning
- Deep Learning
- Data Science
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.
For more information, visit AQEMIA.com, our WTTJ Page , and our LinkedIn .
About our Team
AQEMIA brings together a diverse, multidisciplinary team of 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.
About our Platform Department
The Platform team (~20 people) brings together multidisciplinary teams working on the scientific core of Aqemia’s drug discovery engine. Its mission is to build scalable and reproducible workflows enabling multiple drug discovery programs to run in parallel with minimal manual intervention.
The team combines expertise across Artificial Intelligence and Machine Learning (both research and applications), data science, statistical physics and molecular simulations, computational chemistry (CADD), and other scientific disciplines. Together, they develop predictive models, physics-based simulations, and robust scientific pipelines that power AQEMIA's discovery platform.
At the center of this ecosystem is the “Rocket Launcher” process: an industrialized workflow continuously launching, testing, and improving drug discovery projects through iterative scientific feedback loops.
The role
We are looking for an Applied AI Research Scientist to join Aqemia’s Drug Discovery Platform, working at the intersection of ML and molecular science. You’ll split your time between:
50% AI Research: Develop cutting-edge ML models (e.g., GNNs, generative models, physics-informed AI) to predict molecular properties and protein-ligand interactions.
50% Applied AI: Build ML models that drive real decisions in our internal and partnered drug discovery programs, working hand in hand with chemists, biologists and project leads.
Responsibilities
AI Research & Development (50%)
Design and implement novel Deep Learning algorithms (GNNs, generative, physics-based models).
Take part in cutting-edge research and bibliographic exploration
Collaborate with research and drug discovery teams to translate models into actionable insights.
Applied ML for Discovery Programs (50%)
Develop robust ML models (regression, ranking) from molecular and biological data.
Collaborate with chemists and biologists; deliver results that drive compound prioritization.
Own ML workstreams from start to finish: goals, timelines and stakeholder communication.
Deliver models and pred
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