You apply advanced machine learning and AI methods to multi-modal biomedical datasets to support drug target and biomarker discovery in oncology research.

Your 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

What you bring

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

Conditions

Workload: 100 %
Work model: On site
Option of a permanent position after the assignment if both sides want it

What to expect

Onsite role based in Basel
Relocation support offered
3–6 months interim, then a permanent position

Technologies

PyTorch
Python

How to apply

You apply with your Try&Hire profile: upload your CV, check the details, enter key facts and availability. A short introduction video is optional but helps. Our team will get in touch if your profile fits the assignment.

AI Scientist – AI-Driven Target Identification