AI Scientist

Role Summary

We are seeking an enthusiastic AI/ML scientist with curiosity about pre-clinical and clinical drug development to help accelerate oncology drug discovery programs within the Oncology Data Science team at NBR Oncology. Design and apply AI/ML methods to enable predictive insights from diverse datasets and contribute to transformative medicines for oncology patients worldwide.

Responsibilities

• Design, develop, implement and apply advanced machine learning algorithms, AI models, and platforms to deliver predictive insights from pre-clinical, clinical and real-world evidence datasets.
• Demonstrate value of innovative AI techniques in 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.

Qualifications

• This position will be located at either the Cambridge, MA or Basel, Switzerland site and will not have the ability to be located remotely. This position will require 0-3% travel as defined by the business (domestic and/ or international).
• MSc or Ph.D. in Machine Learning, Computer Science, Applied Mathematics, Computational Biology or related field; PhD preferred.
• Minimum of 0-3 years of experience.
• 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.
• Prior experience working with omics data and familiarity with oncology drug development.
• 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.

Skills

• Machine learning and AI model development
• Generative AI, multi-modal and foundation models
• PyTorch and deep learning frameworks
• Data handling for omics datasets
• Communication of complex insights to cross-functional teams
• Research and publication experience

Education

• MSc or Ph.D. in relevant field (PhD preferred)