Applied AI Scientist
Posted Updated
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% Applied AI: Contribute directly to internal and partnered drug discovery programs by applying ML rigorously and efficiently in collaboration with chemists and project teams.
50% AI Research: Develop cutting-edge ML models (e.g., GNNs, generative models, physics-informed AI) to predict molecular properties and protein-ligand interactions.
Responsibilities:
Applied ML for Discovery Programs (50%)
- Own ML workstreams: define goals, manage timelines, communicate with stakeholders.
- Process molecular datasets and apply robust ML models (QSAR, regression, ranking).
- Collaborate with chemists and project leads; deliver results that drive compound prioritisation.
- Make your models and predictions easily accessible to end users ensuring practical usability in drug discovery workflows.
AI Research & Development (50%)
- Design and implement novel ML algorithms (DL, 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.
Requirements:
- Strong problem-solving skills, autonomy and a collaborative mindset.
- MSc or PhD in Computer Science, Machine Learning, Maths, Physics, or related field.
- ~3-5 years of experience applying ML in scientific or industrial settings.
- Strong experience with ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn).
- Solid Python programming skills and experience working with scientific computing libraries.
Nice-to-Haves
- Experience with bio/health data
Preferred Mindset
- 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.
Please note that applications for this role will close on September 14th, 2026.
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. Collaborations with top Pharma, including a $140M Sanofi deal.
World-Class Interdisciplinary Team : work alongside exceptional talent at the intersection of technology and life sciences. Our teams combine deep expertise in AI, physics-based modeling, biology, and medicinal chemistry to push the boundaries of innovation.
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 : $100M raised from leading European and International investors
What they ask for
Required
- Strong problem-solving skills, autonomy and a collaborative mindset.
- MSc or PhD in Computer Science, Machine Learning, Maths, Physics, or related field.
- ~3-5 years of experience applying ML in scientific or industrial settings.
- Strong experience with ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn).
- Solid Python programming skills and experience working with scientific computing libraries.
Preferred
- Experience with bio/health data
Skills
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