AI Scientist: Target Discovery in Oncology

Novartis; United States; On-site; USD 104,000 - 192,000; Full time

Benefits offered by this job

Hybrid/onsite work options

15+ weeks parental leave

Job summary

Novartis is seeking an AI/ML scientist to join the Oncology Data Science team within Biomedical Research in Cambridge or Basel. The role focuses on applying advanced AI to multi-modal data to advance target and biomarker discovery, with collaboration across drug discovery teams.

Candidates should have a PhD and strong experience in generative AI, foundation models, and multi-modal learning, with proficiency in PyTorch and a track record of publications. Relocation and onsite work are offered.

Qualifications

• PhD in Machine Learning, Computer Science, Applied Mathematics, Computational Biology or related field.
• Strong experience with generative AI, foundation models, multi-modal learning or related areas.
• Experience in PyTorch and ML model deployment.

Responsibilities

• Design, develop, and apply advanced AI/ML approaches to extract insights from datasets across pre-clinical, clinical, and real-world evidence.
• Demonstrate value of AI techniques in drug target ID, biomarker discovery, and biomolecular modeling.
• Work with foundational models to advance generative AI in drug discovery.
• Collaborate with cross-functional teams to enable ML-ready data and practices.
• Publish results and present at scientific venues.

Skills

Generative AI

Foundation models

Geometric DL

Multi-modal learning

Knowledge graphs

PyTorch

ML deployment

Education

PhD in ML/CS/Math/Computational Biology

Tools

Python

Job description

Novartis is seeking an AI/ML scientist to join the Oncology Data Science team within Biomedical Research in Cambridge or Basel. The role focuses on applying advanced AI to multi-modal data to advance target and biomarker discovery, with collaboration across drug discovery teams.

Candidates should have a PhD and strong experience in generative AI, foundation models, and multi-modal learning, with proficiency in PyTorch and a track record of publications. Relocation and onsite work are offered.