Aqemia is an in silico drug discovery start-up, whose ambition is to discover rapidly more innovative therapeutic molecules with better chances of success. How? Just like an AI can learn to play chess, Aqemia’s generative AI learns to invent relevant compounds thanks to unique Statistical Mechanics algorithms predicting drug-target affinity among other properties. Aqemia’s differentiation lies in its affinity prediction both accurate and 10 000x faster than competition, enabling efficient guidance of generation towards compounds with better chances to become drugs.
Aqemia is a spin-off of the École Normale Supérieure Paris leveraging disruptive algorithms from 8 years of research. Aqemia’s team is composed of a dozen of high profiles at the crossroads of Medicinal Chemistry, Statistical Mechanics and Artificial Intelligence.
Founded in June 2019, we have raised €1.6M with leading VC fund Elaia Partners, Bpifrance.
We’re looking for a
Junior & Senior Data Scientist / Machine Learning Engineer [Full Time, ASAP]
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 drug hunters, physicists, chemists and ML engineers
If this sounds exciting to you, come and join us!
As a Data Scientist/Machine Learning engineer, you will develop screening or generative algorithms to design new drug molecules, guided by our proprietary scoring of affinity. You will participate in a shift of paradigm in drug discovery: from database screening to de novo drug design.
You will join a team of 4-5 ML engineers and work directly with clients on projects while developing cutting-edge methods to solve difficult problems.
Your day-to-day responsibilities:
- Work in drug discovery projects along chemists
- Work and code collaboratively
- Implement cutting-edge ML methods to improve docking, large database screening, active learning, molecule generative models, etc.
- Test and benchmark your newly implemented methods
- You have experience in Machine Learning engineering
- Ideally on state of the art embeddings and deep learning
- Based on complex and large data e.g., NLP, complex image, graphs
- You have basic knowledge and sincere interest in biology, physics and chemistry
- You are a pragmatic person, choosing the most impacting method much more than the nicest one
- You’re ready to work in teams on projects with pharmaceutical companies
- You’re a proactive and thorough person
- You’re willing to be part of a multidisciplinary team, and to adapt your ML knowledge to complex physics and chemistry problems
Nice to have:
- Cloud computing experience e.g., AWS or GCP is a plus
You should join us if…
- You are passionate about solving difficult problems on topics that really matter, involving chemistry and biology
- You are curious, willingful and dynamic
- You want to grow and help others grow as well
- You like working collaboratively in an interdisciplinary, fast-paced environment
- You believe in silico/AI can have strong impact on how to find new drugs
- You want to join a small team to bring your own impact in drug discovery
To apply, send us your CV: email@example.com
Aqemia is growing fast. You do not fit in this job description but are excited by this adventure? Contact us!
Aqemia is committed to provide equal employment opportunities regardless of race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity or any other basis as protected by applicable law.