Role overview
We’re an R&D-driven, AI-powered biopharma company committed to improving people’s lives and delivering compelling growth. Our deep understanding of the immune system – and innovative pipeline – enables us to invent medicines and vaccines that treat and protect millions of people around the world. Together, we chase the miracles of science to improve people’s lives.
What you'll work on
- Conducting literature research and internalizing state‑of‑the‑art AI algorithms; implement AI tools for efficient internalization of external data to increase efficiency in drug development.
- Supporting the analysis of high‑dimensional biomarker data using a broad range of ML methods (Random Forest, Gradient Boosting, SVM, recent meta‑learners, etc.) to identify predictive and pharmacodynamic biomarkers.
- Integrating multi‑omics data using deep learning algorithms to better understand mechanisms of action of innovative drugs.
- Developing standard R and Python functions, as well as R Shiny applications, to share methods and results with study teams.
- Collaborating with diverse partners: programmers, biologists, clinicians, bioinformaticians, and more.
- Contributing to a cross‑company working group on ML/AI applications in drug development, with emphasis on biomarker science.
- Sharing findings through scientific publications, seminars, and internal/external webinars.
*About you
Experience:**
- At least 1 year of experience with R programming.
- Experience with transcriptomic data is highly preferred.
What we're looking for
- Strong foundation in statistics and/or bioinformatics.
- Good understanding of deep learning and AI.
- Good knowledge of Python.
- Autonomous, rigor, team player.
Tags & focus areas
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