Advisor - Cheminformatics & Computational Chemistry

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve.

This is hard, urgent, selfless work-but it's work worth doing. If you're driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.

Lilly Catalyze
360 is a comprehensive approach to enabling the early-stage biotech ecosystem by democratizing access to infrastructure, expertise, and resources. Through its interconnected pillars-Lilly Ventures, Lilly Gateway Labs, Lilly ExploR&D, and Lilly Tune Lab-Catalyze
360 strategically removes barriers that traditionally block bold science from becoming life-changing medicines, providing biotechs with flexible combinations of capital, physical lab space, R&D capabilities, AI/ML tools, and decades of enterprise learning.

Lilly Tune Lab is an artificial intelligence and machine learning (AI/ML) platform that provides biotech companies access to drug discovery models trained on years of Lilly's research data. Lilly estimates that this first release of AI models includes proprietary data obtained at a cost of over $1 billion, representing one of the industry's most valuable datasets used to train an AI system available to participating companies.

By integrating advanced in silico modelling and federated learning, we connect pioneering machine learning algorithms, substantial computational power, exclusive datasets, and Lilly's domain-specific knowledge to drive innovation in drug discovery and facilitate access to optimal therapies for patients.

We are seeking a highly motivated Cheminformatics/Computational Chemistry Scientist to design, evaluate, and build end-to-end small molecule computational workflows within the Tune Lab platform. This role requires strong hands-on expertise in state-of-the-art computational methods across the drug discovery pipeline, from virtual screening to lead optimization.

You will work at the intersection of cheminformatics, physics-based modeling, and machine learning, partnering closely with Tune Lab software engineering and ML teams to deliver scalable, production-grade workflows.

This is a high-impact role, where you will independently evaluate tools, make build-vs-buy decisions, and deliver robust workflow solutions.

Design and implement workflows spanning:

• Virtual screening (ligand-based and structure-based)
• Hit identification and hit expansion
• Hit-to-lead selection
• Lead optimization

Apply and integrate core computational chemistry and cheminformatics methods, including:

• Ultra-large library search:
  • Substructure search
  • Fingerprint and embedding-based similarity search
  • Shape and pharmacophore-based screening
• Molecular enumeration:
  • Reaction-based enumeration
  • Fragment-based design and expansion