Lilly is looking to solve the problem of discovering and developing life-changing medicines for people around the world, specifically in the area of small molecule discovery, by applying cutting-edge science and technologies to unlock new approaches for treating diseases with poor treatment options.
Requirements
- PhD in Cheminformatics, Computational Chemistry, or related field with 7+ years relevant research and/or industrial experience.
- Track record of successfully applying and developing cheminformatics workflows and tools that accelerate hit finding, hit expansion, lead generation and library design efforts.
- Expertise in data analytics, ML/AI modelling in the context of cheminformatics and a solid grasp of statistical principles.
- Strong scientific programming skills (Python essential) and experience building data visualizations and dashboards (e.g., in Spotfire).
- Excellent understanding of the phases of drug discovery from target assessment through to candidate selection and the fundamental concepts of drug design, medicinal chemistry and ADME.
- Good appreciation of computational chemistry and organic chemistry.
- Familiarity with Large Language Models (LLMs).
Responsibilities
- Lead from the bench by judiciously building up and applying state of the art cheminformatics, ML/AI, and advanced analyses capabilities, to enable library design, hit identification, prioritization and hit-to-lead progression across multiple target classes and modalities.
- Provide scientific leadership and strategic guidance on cheminformatics and applied ML/AI approaches to drive data driven drug discovery.
- Encourage close collaborations and initiatives with computational colleagues, medicinal chemists and other cross function partners that culminate in the generation of well poised screening collections, quality models and testable hypotheses, enhancing our ability to deliver differentiated quality hits and leads.
- Ensure team success by providing guidance on the application of modern cheminformatics, ML/AI methods for: library design (e.g. diversity, focused, bridging, fragment, DEL collections); analyzing large datasets (e.g. from HTS campaigns or omics data sets) and building predictive (active learning) models from them; data mining internal and external data-sets/bases; enabling hit prioritization and expansion efforts; guiding ligand-/fragment-based design activities.
- Provide cheminformatics insight for new target identification and evaluation initiatives in the early space across a range of targets and binding mode types.
- Proactively investigate new technologies that have the potential to accelerate EMD’s ability to prosecute challenging targets and deliver quality differentiated leads.
- Develop synthon-based search strategies to allow teams to leverage ever increasing virtual spaces without having to rely on brute force searches of fully enumerated spaces.
Other
- Ability to create, sustain and model a culture of innovation, collaboration and dedication.
- Aptitude for building inclusive teams and commitment to mentoring early career computational chemists.
- Demonstrated ability to identify and effectively champion new technologies culminating in successful drug discovery applications thereof.
- Proactive in establishing and driving effective collaborations with medicinal chemists and scientists form other disciplines to achieve project goals and timelines.
- Ability to communicate effectively with team members, cross-functional colleagues and senior leadership.
