Description
You apply advanced machine learning and AI methods to multi-modal biomedical datasets to support drug target and biomarker discovery in oncology research.
Tasks
- Design and implement machine learning algorithms and AI models for predictive insights
- Apply AI techniques to drug target identification and biomarker discovery
- Work with foundational, pre-trained and multi-modal models for generative AI applications
- Collaborate with cross-functional teams on ML-ready data practices
- Contribute to scientific publications and present at conferences
Profile
- Ph.D. in Machine Learning, Computer Science, Applied Mathematics, Computational Biology or related field
- Experience in generative AI, biomedical foundation models, geometric deep learning or multi-modal learning
- Strong programming skills and proficiency in deep learning frameworks such as PyTorch
- Practical experience across the ML and LLM software stack, including deployment and validation
- Experience with omics data and familiarity with oncology drug development
- Publications in top-tier ML/AI conferences or leading scientific journals
Offer
- Onsite role based in Basel
- Relocation support offered
- 3–6 months interim, then a permanent position
Company
Pharmaceutical research