About Novartis

Novartis is a global biopharmaceutical company that researches, develops, manufactures, and markets prescription drugs in areas including oncology, immunology, neuroscience, and cardiology. Industry: Biopharmaceuticals

Novartis currently has 17 open roles on FindRole.

Listed pay typically runs $160,300–$297,700 across 17 roles with salary data.

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At a glance

TL;DR · Associate Director and Senior Principal, AI Methods, AI for Research

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As an Associate Director and Senior Principal in the AI Methods group at AI for Research (AI4R) in Cambridge, USA, you will lead matrixed teams to develop advanced machine learning solutions that accelerate drug discovery. Your day-to-day responsibilities include designing robust algorithms, models, and workflows, establishing strategic collaborations with external partners, and translating complex model outputs into actionable scientific hypotheses. You will need hands-on experience with large-scale model training, high-performance computing, and cloud infrastructure, along with proficiency in Python and deep learning frameworks like TensorFlow or PyTorch. This role requires a strong background in applying machine learning to target identification, protein modeling, and translational research within the biomedical domain, aiming to redefine how AI transforms healthcare through innovative medicines.

Skills

Python Deep Learning Machine Learning Pandas R Programming SQL Terraform Kubernetes AWS CI/CD Git Scikit-learn TensorFlow PyTorch Docker Prometheus Grafana

What you'll do

Lead teams in designing and delivering robust machine learning solutions for drug discovery.
Drive development of core machine learning capabilities across priority AI use cases.
Identify opportunities for methodological innovation throughout the drug discovery pipeline.
Build advanced algorithms to accelerate therapeutic discovery and development.
Establish strategic collaborations with academic and external research partners.

What we're looking for

6+ years of experience in developing and deploying machine learning solutions for drug discovery.
Hands-on expertise with target identification, protein modeling, or translational research using ML.
Strong background in large-scale model training, high-performance computing, and cloud infrastructure.
Advanced knowledge of modern ML methods like representation learning and neural networks.
Proficiency in Python, deep learning frameworks, software development, and version control practices.