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About the Role
As a Senior AI Research Scientist, you will develop cutting-edge AI models to predict molecular properties and protein–ligand interactions. You will be a hands-on technical expert, pushing the boundaries of AI for drug discovery, improving on AlphaFold approaches, and building probabilistic models for Bayesian optimization. You will own a key project, mentor others, and ensure new AI methods become practical tools for drug discovery programs.
Responsibilities
- Develop novel ML models to predict molecular properties and protein–ligand interactions, focusing on accuracy, uncertainty, and generalization.
- Contribute to improving protein–ligand structure prediction by building on and enhancing AlphaFold implementations.
- Build probabilistic deep learning models for Aqemia’s multi-fidelity Bayesian optimisation engine, capturing uncertainty.
- Own a key ML team roadmap project from research and prototyping through to production.
- Identify relevant literature, benchmark promising ideas, and propose model or pipeline improvements.
- Collaborate with AI researchers, computational chemists, and drug discovery teams to translate AI models into actionable scientific insights.
- Mentor team members on model design, implementation, debugging, and best practices.
Requirements
- PhD in Computer Science, Mathematics, Physics, AI/Machine Learning, or a related quantitative field.
- 8+ years of experience in AI/ML research (academia or research-intensive industry).
- Proven track record of developing ML models from scratch and understanding their theoretical and practical workings.
- Strong programming skills in Python and deep learning frameworks (PyTorch, JAX, TensorFlow).
- Demonstrated ownership of research projects and drive to productionize research.
- Strong problem-solving skills, collaborative mindset, and clear communication.
- Experience applying ML to drug discovery (chemistry side) is a plus.
- Hands-on experience with scientific computing libraries (RDKit, OpenMM) is a plus.
- Experience with Bayesian optimisation or uncertainty quantification is a plus.
- Experience productionizing models or with software engineering best practices is a plus.
Skills
- AI/ML
- Deep Learning
- Python
- PyTorch
- JAX
- TensorFlow
- Protein-Ligand Interaction Prediction
- Molecular Property Prediction
- AlphaFold
- Probabilistic Models
- Bayesian Optimization
- Uncertainty Quantification
- Scientific Computing
- RDKit
- OpenMM
- Software Engineering
Location
- Paris
- London
Work Type
- Flexible work arrangements
- Up to two remote days per week
Experience Level
- Senior
Education Level
- PhD
Benefits
- Impact on changing drug discovery
- Shape company direction
- Expanding Drug Discovery Pipeline
- Collaborations with top Pharma
- World-Class Interdisciplinary Team
- DeepTech Recognition
- Prime Location
- Strong Financial Backing
About the Company
- AQEMIA is a drug invention company creating new medicines for unmet medical needs using its proprietary QEMI platform, which combines physics-based modeling, statistical mechanics, and generative AI.
- The company focuses on inventing novel molecular entities from first principles, not refining existing ones.
- AQEMIA's preclinical programs target diseases lacking effective treatments.
- AQEMIA has a diverse, multidisciplinary team of 80+ professionals in Paris and London, including chemists, physicists, machine learning experts, and software engineers.
- The Platform Department (~20 people) builds scalable workflows for drug discovery, integrating expertise in AI/ML, data science, physics, and computational chemistry.
- The "Rocket Launcher" process is an industrialized workflow for iterative drug discovery projects.
- AQEMIA is recognized as a key player in Europe's DeepTech ecosystem, part of French Tech 120 and France 2030.
- The company has raised $100M from leading investors.
Equal Opportunity
- We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.