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.
Responsibilities:
- 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.
- 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.
Skills Required
- MSc or PhD in Computer Science, Machine Learning, Mathematics, Physics, or related field
- Approximately 3-5 years of experience applying ML in scientific or industrial settings
- Strong experience with ML frameworks (PyTorch, TensorFlow, Scikit-learn)
- Solid Python programming skills and experience with scientific computing libraries
- Experience designing and implementing ML algorithms, including GNNs, generative models, and physics-informed approaches
- Experience with bio/health data
- Strong problem-solving skills, autonomy and a collaborative mindset
What We Do
AQEMIA is a next-gen pharmatech company generating one of the world's fastest-growing drug discovery pipeline. Our mission is to design fast innovative drug candidates for dozens of critical diseases, such as immuno-oncology. Our unique approach leverages quantum-inspired physics algorithms to power generative AI in designing novel drug candidates—without relying on experimental data. We already delivered several drug discovery successes within our internal pipeline and through collaborations with pharmaceutical companies. Our most advanced programs are currently in vivo optimization. We are growing and hiring! Check our career website: https://jobs.lever.co/aqemia.com Discover the roles and behind-the-scenes at AQEMIA on our Welcome To The Jungle page: https://www.welcometothejungle.com/fr/companies/aqemia
