At DeepLife, our team focus their effort for the development of state-of-the-art deep learning and reinforcement learning techniques in order to accelerate drug discovery. Drug discovery lies in two steps: First, identification of a target which will drive disease cells state toward a healthy state. Second, design of a molecule that will act specifically on the target.
At DeepLife, we are working on AI assisted tools for target identification, which is the first step toward bio-engineering.
We believe that AI assisted bio-engineering is the next major revolution of the 21th century, and we aim to be a pioneer in this field.
Our team is developing digital twins of human cells using sequencing data. Your work is to design the best reinforcement learning algorithm to discover optimal combinations of drugs to cure a given pathology. Your finding will play a major part for a proof-of-concept with one of our partners.
We are looking for a candidate willing to push back boundaries in deep learning and reinforcement learning in order to disrupt the way drug discovery is performed today.
Are you ready to tackle this challenge?
- Written / spoken fluency in English
- Find relevant information and implement algorithms from academic literature
- Strong background in machine learning and renforcement learning
- Master 2, engineer degree or equivalent
- Solid skills in deep learning and applied mathematics
- A real passion for AI
- Experience working with large datasets using Python, Matlab, or other statistical software
- We are committed to partner with the academic community and publish our work in the best international conferences.
- This internship may lead to a PhD or a R&D engineer full time position
- Website: www.deeplife.co
- Localization: Station F - 5 Parvis Alan Turing, 75013 Paris