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 - Machine Learning and Deep Learning
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!
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 :
- Generation of molecules in a constrained chemical space.
- Development of interpretable predictors of molecular properties.
- Multi Constraint Optimization strategies to generate molecules that satisfy several criteria.
- Representation learning on molecules : unsupervised or semi-supervised techniques to learn embeddings of molecules.
- Active learning strategies to decide when to acquire new data or to use model prediction.
- You are a Masters student in Computer Science or applied mathematics.
- Ideally with hands-on experience in representation learning, generative models, reinforcement learning.
- Interest for complex data such as graphs, text, 3D objects / point-clouds.
- Interest for unsupervised learning, low-data tasks and active learning.
- With experience in reading academic papers and exercising critical thinking on results.
Nice to have:
- Basic knowledge in biology and chemistry 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 email@example.com.