About AQEMIA

AQEMIA is a next-gen pharmatech company generating one of the world's fastest-growing drug discovery pipeline.

Our mission is to design fast innovative drug candidates for dozens of critical diseases, such as immuno-oncology.

Our unique approach leverages quantum-inspired physics algorithms to power generative AI in designing novel drug candidates—without relying on experimental data.

We already delivered several drug discovery successes within our internal pipeline and through collaborations with pharmaceutical companies. Our most advanced programs are currently in vivo optimization.

About the team you will join

As a Machine Learning Research Intern, you’ll join a team of engineers and researchers building algorithms to improve and accelerate our internal drug discovery pipeline. You will be working in the series-expansion team, composed of 3 ML engineers. On a day-to-day basis, you will interact with Victor Saillant.

Your role

You will explore the topic of molecular generation in depth and be responsible for literature review, implementation and training/evaluation of models on public and proprietary data. 

Your internship should last between 4 and 6 months, and can start as early as possible.

Subject of the internship

The objective of the internship is to address the problem of molecule generation conditioned on a protein, and possibly in a constrained chemical space and additional physico-chemical properties. The proposed method involves the use of diffusion models on graphs to address this issue (see references [1][2]). Additionally, alternative approaches, like auto-regressive models, may be explored in a subsequent phase (see references [3][4]).

Skills

Nice to have

Why Join Us ?

At AQEMIA, we work for a mission: joining us means having your own impact on changing the way drugs are discovered, and helping to shape the direction of our fast-growing company and team.

Expanding Drug Discovery Pipeline : Focused on critical diseases like immuno-oncology, with in vivo proof of concept/patent stage programs. Collaborations with top Pharma, including a $140M Sanofi deal.

Interdisciplinary Team : brilliant talent from tech and life sciences.

Experienced Leadership : Founders with 15+ years at ENS, Oxford, Cambridge, and BCG.

DeepTech Recognition: Part of French Tech 120 and France 2030.

Prime Location : Based in central Paris with the possibility of 2 remote days per week.

International Environment : English-speaking team with relocation support and French lessons if needed.

Strong Financial Backing : $60M raised from leading European deeptech investors