Staff AI Research Scientist

About AQEMIA AQEMIA is a drug invention company dedicated to creating entirely new medicines to address major unmet medical needs. Our research focuses on inventing never‑before‑seen molecules using our proprietary QEMI platform that blends physics‑based modeling, statistical mechanics, and generative AI.

The role

As a Staff AI Research Scientist you’ll join the Drug Discovery Platform Teams, leading the development of cutting‑edge AI algorithms for modelling protein‑ligand systems. You’ll collaborate closely with AI researchers, computational chemists, and drug discovery experts to integrate your innovations directly into our platform and accelerate the discovery of novel therapeutics.

You will be

• Be a technical leader – Drive the development of cutting‑edge AI 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 (AI, computational chemistry, and drug discovery experts) to translate AI research into real‑world impact.

What you’ll do

• Lead research initiatives to develop and apply novel AI models for molecular modeling, protein‑ligand interactions in drug discovery.
• Design and implement advanced machine learning techniques, including deep learning, generative models, graph neural networks, and physics‑informed AI to predict molecular properties and interactions.
• Collaborate with interdisciplinary teams, including computational chemists, physicists, and medicinal chemists, to integrate AI‑driven solutions into real‑world drug discovery pipelines.
• Scale AI models for real‑world applications, optimizing model efficiency, interpretability, and generalization to unseen chemical spaces.
• Mentor and guide junior researchers and engineers, fostering a culture of scientific innovation and excellence.

What we’re looking for

• PhD or equivalent practical experience in AI/ML, Mathematics, Physics, Computational Chemistry or a related field.
• Strong problem‑solving skills, autonomy and a collaborative mindset.
• Expertise in machine learning applied to proteins, small molecules, and molecular simulations.
• Strong programming skills in Python and proficiency with ML frameworks (e.g., PyTorch, JAX, TensorFlow).
• Hands‑on experience with scientific computing libraries (e.g., RDKit, OpenMM) and molecular representations (e.g., SMILES, molecular graphs, 3D structures).
• Ability to bridge AI research with practical drug discovery challenges, designing scalable and interpretable models.

Nice‑to‑have qualifications

• Experience with physics‑informed ML models.
• Background in free energy calculations, docking, or molecular property prediction.
• Familiarity with high‑performance computing (HPC) and cloud‑based ML pipelines.

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 highly scientific challenges – Enthusiasm for tackling complex problems at the frontier of AI and drug discovery.
• Synergy minded – A collaborative spirit, thriving in an interdisciplinary environment.
• Humility – Open to feedback and different perspectives, always striving for improvement.

Benefits

• Prime location in Paris and London (King’s Cross) with flexible work arrangements, including up to two remote days per week.
• World‑class interdisciplinary team combining deep expertise in AI, physics‑based modeling, biology, and medicinal chemistry.
• Strong financial backing – €100 M raised from leading European and international investors.
• Opportunity to work on critical therapeutic areas such as oncology, CNS, and immuno‑inflammation with in‑vivo proof‑of‑concept programs and major pharma collaborations.