Applied AI Research Scientist (Drug Discovery)

Location: Paris, France; hybrid workplace with up to two remote days per week

Company

A drug invention company developing novel medicines through physics-based modeling, statistical mechanics, generative AI, and its proprietary QEMI molecule-invention platform.

What you will do

• Design and implement deep learning algorithms, including graph neural networks, generative models, and physics-based models.
• Develop regression and ranking models using molecular and biological data.
• Predict molecular properties and protein-ligand interactions for drug discovery programs.
• Collaborate with chemists, biologists, research teams, and project leads to translate models into actionable insights.
• Own ML workstreams end to end, including goals, timelines, stakeholder communication, and delivery.
• Deliver models and predictions that support compound prioritization and daily scientific workflows.

Requirements

• MSc or PhD in Computer Science, Machine Learning, Computational Chemistry, or a related field.
• Approximately 3–5 years of experience applying machine learning in scientific or industrial settings.
• Strong experience with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn.
• Strong Python programming skills and experience with scientific computing libraries.
• Strong problem-solving skills, autonomy, and a collaborative mindset.

Nice to have

• Experience in drug discovery, computational chemistry, or physics.
• Experience with diffusion models, variational autoencoders, or autoregressive models applied to structured data.
• Familiarity with structure-based drug design and protein-ligand interactions.
• Familiarity with high-performance computing and cloud-based ML pipelines.

Culture & Benefits

• Work at the intersection of AI, physics-based modeling, biology, medicinal chemistry, and life sciences.
• Contribute to drug discovery programs in oncology, CNS, and immuno-inflammation.
• Collaborate with leading pharmaceutical companies through strategic partnerships.
• Flexible hybrid arrangements with up to two remote days per week.
• Offices in Paris and London.