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

I Suoi compiti

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

Che cosa porta con sé

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

Condizioni quadro

Grado di occupazione: 100 %
Modello di lavoro: In sede
Opzione di assunzione a tempo indeterminato dopo l'incarico, se entrambe le parti lo desiderano

Che cosa La aspetta

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

Tecnologie

PyTorch
Python

Come candidarsi

Si candida con il Suo profilo Try&Hire: carichi il CV, verifichi i dati, inserisca i dati principali e la disponibilità. Un breve video di presentazione è facoltativo, ma aiuta. Il nostro team La contatterà se il Suo profilo è adatto all'incarico.

AI Scientist – AI-Driven Target Identification