Computational Chemistry Scientist

Servier

Gif-sur-Yvette, France

About the role:

The primary objective is to provide expert support to therapeutic research projects by leveraging cutting-edge Computational Chemistry approaches with a strong focus on Artificial Intelligence and Cloud Computing technologies. In partnership with the Chemistry, Data Science and Data Factory internal stakeholders, the successful candidate will be a key driver in applying AI methods to accelerate the discovery of new innovative molecular entities. They will actively participate in the implementation of new AI-based technologies and lead the technical upskilling of the team on Cloud environments.

Your main responsibilities:

Implement and deploy new AI technologies specifically applied to the design of bioactive molecules, including generative and predictive approaches. Ensure new initiatives appear in the AI Roadmap and influence development directions.
Devise and execute computational chemistry strategies to design new bioactive molecules using advanced molecular modeling, chemoinformatics and Machine Learning techniques. Explore small molecules and biologics modalities, including monoclonal antibodies (mAb) and PROTACS.
Establish strong partnerships and provide quality support to internal stakeholders of the Computational Chemistry team, particularly: Medicinal Chemistry team leaders, the Pole of Activity Data Science Data Management and the ADME/Tox department.
Deploy and maintain development environments (Anaconda, Jupyter Notebook) in the cloud environment on GCP. Use Docker files to create reproducible and portable computing environments.
Contribute to the team's GitHub, ensuring best practices for versioning and sharing Python code. Lead the training and upskilling of Computational Chemistry team members on Cloud technologies.

What we’re looking for:

Background:
- PhD in Machine Learning for Drug Discovery or in Computational Chemistry. 2–3 years of proven experience leveraging cloud-based technologies within an industrial setting.
Hard Skills:
- Demonstrated skills in Machine Learning and Cloud technologies.
- Solid knowledge in computer-aided design of bioactive molecules across a range of biological target classes.
- Good proficiency in Python (Data Science stack).
- Familiarity with Anaconda, Jupyter Notebook, and GitHub.
- Knowledge of containerization concepts (Docker).
- Familiarity with pharmacology and medicinal chemistry concepts.
- Track record of scientific contributions, including as the first author in peer-reviewed publications.
- Language skills : Strong oral and written communication skills in English (preferably also in French).
Soft skills:
- Ability to work collaboratively in a team-oriented environment, with full autonomy.
- Aptitude for tackling challenging questions and developing bold and creative solutions in drug discovery.
- Strong capacity for knowledge transfer and upskilling team members on emerging AI technologies and methodologies.