Research Intern - Computational Chemistry and Structural Biology

About Aqemia

Aqemia’s ambition is to discover better and more innovative therapeutic molecules faster. Better  molecules because our physics-based technology has unparalleled precision. More innovative molecules because we don’t rely on past data, we’re not stuck to staying close to what already exists. Faster because our precision implies less experiments.In a nutshell, we’re building a new type of massive, internal drug discovery pipeline.

We’re looking for a 

Research Intern - Computational Chemistry and Structural Biology

to join our core team and make an impact on a critical challenge: discovering drug candidates to cure key diseases. You will work in an interdisciplinary team of in silico drug hunters, physicists, medicinal chemists and machine learning engineers.

Founded in June 2019, we have raised $10M with leading VCs.

If this sounds exciting to you, come and join us!

Job description

As a research intern, you will explore in depth a particular topic, all the way from literature review to testing your approach on proprietary data. We are willing to discuss the choice of the topic so that it best fits your expertise, but it could include : 

  • Structural Biology studies of key target proteins
  • Development of Docking strategies with state of the art technologies
  • Free Binding Energy calculations with Aqemia core technology
  • Representation learning on molecules : unsupervised or semi-supervised techniques to learn embeddings of molecules. 
  • Multi Constraint Optimization strategies to generate molecules that satisfy several criteria.
  • Development of interpretable predictors of molecular properties. 

Your profile

  • You are a Masters student in Computational Chemistry, Theoretical Chemistry or Structural Biology  
  • Ideally with hands-on experience in Computational Chemistry techniques and softwares (Docking, Molecular Dynamics, …)
  • Interest for protein-ligand interaction and Structural Biology. 
  • With experience in reading academic papers and exercising critical thinking on results.

Nice to have:

  • Basic knowledge in machine learning and drug discovery is a strong plus, but it is not required.

You should join us if…

  • You are passionate about solving difficult problems on topics that really matter
  • You are curious, willingful and dynamic
  • You like working collaboratively in an interdisciplinary, fast-paced environment
  • You want to join a small team to bring your own impact in drug discovery

To apply, send us your CV at