AI Scientist — Target Discovery for Oncology

Novartis; Cambridge (MA); On-site; USD 103,600 - 192,400; Full time

Benefits offered by this job

Insurance plans

Retirement plans

Wellbeing resources

Global recognition programs

Flexible & hybrid work

14 weeks parental leave

Job summary

Novartis is seeking an AI/ML scientist for the Oncology Data Science team in Biomedical Research. The role focuses on applying advanced AI to multi-modal datasets to advance target and biomarker discovery, and to develop generative AI applications for drug discovery.

The candidate will collaborate across cross-functional teams, contribute to publications, and work with foundational models to push the frontier of AI in oncology. Relocation is offered; onsite in Cambridge or Basel.

Qualifications

• PhD required in ML/CS/Applied Math/Computational Biology or related field.
• Strong experience in generative AI, foundation models, and multi-modal learning.
• Proficiency in PyTorch and ML/LLM stack; able to deploy and validate models.

Responsibilities

• Design and apply advanced AI/ML to multi-modal biomedical datasets.
• Demonstrate value of AI in target identification and biomarker discovery.
• Work with foundational models to advance generative AI in drug discovery.
• Collaborate with cross-functional teams to prepare ML-ready data.
• Contribute to scientific publications and present results.

Skills

Generative AI

Biomedical foundation models

Geometric deep learning

Multimodal learning

Knowledge graphs

PyTorch

ML/LLM stack

Omics data

Oncology drug development

Communication

Research publications

Education

PhD in ML/CS/Applied Math/Computational Biology or related field

Tools

PyTorch

Job description

Novartis is seeking an AI/ML scientist for the Oncology Data Science team in Biomedical Research. The role focuses on applying advanced AI to multi-modal datasets to advance target and biomarker discovery, and to develop generative AI applications for drug discovery.

The candidate will collaborate across cross-functional teams, contribute to publications, and work with foundational models to push the frontier of AI in oncology. Relocation is offered; onsite in Cambridge or Basel.