AI Scientist

Job Description Summary

#LI-Hybrid
Location: Basel, Switzerland or Cambridge, US.
The Oncology Data Science team in Novartis Biomedical Research (NBR) provides computational biology, AI and data engineering expertise to the Oncology Disease Area across a wide and unique range of novel therapeutics spanning many different drug modalities. Our mission is to harness the transformative power of data and AI to accelerate the development of innovative and transformative medicines for oncology patients worldwide.
We are seeking an enthusiastic AI/ML scientist with curiosity about pre-clinical and clinical drug development to help us accelerate our ground-breaking oncology drug discovery programs. You will join the Oncology Data Science team at NBR Oncology, an outstanding collaborative environment with supportive and enthusiastic colleagues who will help your AI models achieve real-world impact.

 

Job Description

Key responsibilities:

• Design, develop, implement and apply advanced machine learning algorithms, AI models, and platforms to enable the delivery of predictive insights from pre-clinical, clinical and real-world evidence datasets.
• Demonstrate value of innovative AI techniques in the context of drug target identification, biomolecular interaction modeling, drug development, biomarker discovery, treatment response prediction and clinical trial design.
• Work with foundational models, including pre-trained, self-supervised, multi-purpose, and multi-modal models to advance generative AI applications in drug discovery.
• Collaborate with cross-functional teams to develop and adopt best practices for ML-ready data.
• Contribute to scientific publications and present results at internal and external scientific conferences.

Minimum Requirements:

• MSc or Ph.D. in Machine Learning, Computer Science, Applied Mathematics, Computational Biology or related field; PhD preferred.
• Strong experience in one or more of the following areas: generative AI, agentic AI, biomedical foundation models, geometric deep learning, multi-modal learning, and large-scale knowledge graphs.
• Excellent programming skills and proficiency in deep learning frameworks (PyTorch), with openness to learning new tools and technologies.
• Practical experience across ML and Large Language Models (LLMs) software stack, including feature engineering, model development, deployment, and validation.
• Excellent communication skills, with the ability to communicate complex data insights and recommendations to cross-functional teams and stakeholders.
• Demonstrated strong research skills, evidenced by publications in top-tier machine learning or artificial intelligence conferences and/or leading scientific journals.

Nice to have:

• Prior experience working with omics data and familiarity with oncology drug development is desirable

Commitment to Diversity & Inclusion:

We are committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.

Benefits and rewards:

Read our handbook to learn about all the ways we’ll help you thrive personally and professionally:

https://www.novartis.com/careers/benefits-rewards

Novartis is committed to working with and providing reasonable accommodation to all individuals. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the recruitment process, or in order to receive more detailed information about the essential functions of a position, please send an e-mail to [email protected] and let us know the nature of your request and your contact information. Please include the job requisition number in your message. 

 

Skills Desired

Biostatistics, Computer Programming, Data Analysis, Databases, Data Management, Data Mining, Data Quality, Data Visualization, Deep Learning, Graph Algorithms, High-Performance Computing, Logistic Regression Model, Machine Learning (Ml), Master Data Management, Pandas (Python), Python (Programming Language), R (Programming Language), Random Forest Algorithm, Sql (Structured Query Language), Statistical Modeling, Time Series Analysis