Stagiaire Computational Chemistry (H/F)
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We are a human-sized, international, independent pharmaceutical group governed by a Foundation. We are proud of our unique model, which above all allows us to fully serve our mission: "committed to therapeutic progress for the benefit of patients ."
As a global leader in cardiology, we have chosen to become a focused and innovative player in oncology by 2030, targeting difficult-to-treat cancers and devoting more than 70% of our R&D budget to this area.
Who are we? 21,900 passionate individuals from more than 50 countries, driven by an entrepreneurial spirit. Every day, we move forward with and for our patients, with and for our teams, driven by the desire to care, to dare, to grow, and to commit ourselves to helping those in need.
Internship topic: Computational Chemistry internship - AI-Guided Design in Synthon-Based Combinatorial Spaces
Job Description:
We are seeking a highly motivated and curious intern to join our Computational Chemistry group near Paris. The selected candidate will focus on building, implementing, and validating a custom combinatorial library based on commercial and internal chemical building blocks. The project will integrate AI-driven molecular design within these controlled synthon-defined chemical spaces to promote the discovery of synthetically feasible small molecules. This internship offers an exciting opportunity to contribute to innovative research bridging cheminformatics, AI, and synthetic strategy.
Key Responsibilities:
Curate and annotate a synthon database using commercial and internal building blocks and prepare the library in a format compatible with cheminformatics tools for combinatorial exploration.
Implement and evaluate generative molecular design methods within these synthon-defined chemical spaces, optimizing for synthetic accessibility and chemical diversity.
Utilize cheminformatics workflows and scoring functions to analyze and prioritize generated molecules based on design and synthetic feasibility criteria.
Document progress, provide reports, and present results in team meetings, contributing to future integration.
Technical Skills and Qualifications:
Currently pursuing or recently completed a Master’s degree in Computational Chemistry, Chemistry, Cheminformatics, Computer Science, or related field.
Solid understanding of chemoninformatics ; experience with cheminformatics tools such as RDKit or similar is required.
Proficiency in Python for scientific computing and familiarity with Jupyter notebooks.
Exposure to AI and machine learning approaches in chemistry is an advantage.
Strong analytical and problem-solving skills with ability to communicate clearly in writing and presentations.
What We Offer:
Hands-on training in modern cheminformatics and AI-based molecular design workflows.
Collaborative environment with experts in computational chemistry and medicinal chemistry.
Mentoring and opportunities for growth.
Exposure to cutting-edge platforms at the interface of chemistry, computation, and automation.
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