The AI & Computational Science (AICS) is the dedicated AI team at Biomedical Research, Novartis, innovating drug discovery with AI. We aim to accelerate discoveries of transformative medicines for patients worldwide. AICS is seeking a highly motivated technical/scientific leader in the domain of Applied AI to push the frontiers in disease understanding and drug discovery. At AICS, you will create impact at the intersection of science R&D and AI.

• Design, develop, implement, train, test, and refine modern deep learning AI models for data represented as sequences, which may be text, graphs, or biological sequences (e.g., DNA, RNA, or proteins)
• Apply deep understanding of foundation models (pre-trained and large language models) to build generative AI applications in biology, chemistry, and text domains.
• Design and develop innovative AI model architectures leveraging principles from encoder/decoders, jointly trained models, Siamese-twin models, VAEs, GANs, etc., and advanced training methods (e.g., GPT, Diffusion), and developing/refining learning objectives including self-supervision.
• Take a hands-on role and deliver on highly visible projects. Conduct applied AI experiments using scientific, rigorous, and reproducible methodology, on internal datasets as well as on public datasets so that the results may be publishable as appropriate.
• Serve as an ambassador for AI/Data Science by presenting and publishing articles. Build a bridge between academia, technology, and industry partners.
• Keep ahead of latest developments in the field and mentor associates. Be a part of a truly unique organization, work with an inter-disciplinary team of highly accomplished scientists and push the AI frontiers for disease understanding and drug discovery.

• Knowledge of standard AI models, such as Transformers, LSTMs, RNNs, and CNNs, used in NLP and other sequence data domains.
• Experience with LLMs, e.g., prompt-engineering, use of embeddings, and application architectures using LLMs.
• Emerging uses of AI for biology and chemistry leveraging models from NLP. Experience with knowledge graphs and Graph Neural Networks
• Expert level Python or scala programming. Ability to work effectively in a team and “raise the bar” of the team in all aspects.
• Cloud computing optimization for high performance AI model training Explain ability, bias, and ethics in applying AI models.
• Statistical methods necessary to analyze results for AI models (e.g., statistical significance testing). An advanced degree (master’s or doctoral) in computer science or closely related computational field.
• Three or more years of relevant leadership/publication track record in deep learning and applied AI research and application
• 5+ years of experience in end-to-end AI model development for realistic, large scale data sets. Tech industry experience is very relevant, and any experience in pharma, biotech, or healthcare is a plus.