Head of Computational Chemistry - Molecule Discovery

Eli Lilly and Company; Windlesham; On-site; GBP 145,000 - 254,000; Full time

Job summary

Lilly is seeking an expert computational chemist to advance hit-to-lead programs using state‑of‑the‑art virtual screening, AI/ML, and cheminformatics. You will partner with LSMD and ExploR&D to deliver data‑driven designs and robust models that accelerate biotech collaborations.

The role emphasizes leadership, cross‑functional teamwork, and a hands‑on approach to rapidly adapt to diverse targets while advancing novel therapeutics across multiple modalities.

Qualifications

• PhD or equivalent in computational chemistry or related field with extensive experience.
• Proven track record in virtual screening and cheminformatics to accelerate hit discovery.
• Strong programming and data analytics skills, with Python essential.

Responsibilities

• Lead computational chemistry efforts across target classes and modalities.
• Collaborate with biotech partners and cross-functional teams to design workflows.
• Guide library design, hit identification, and lead expansion using ML/AI.
• Develop predictive models and leverage TuneLab platform.
• Communicate goals and priorities across teams; deliver robust designs.
• Support expansion into non-small-molecule modalities (antibodies/RNA) as needed.

Skills

Python programming

Data analysis

Education

PhD in Computational Chemistry, Cheminformatics, CompBiophysics or a related field

MS with 10+ years industry/academic/research

BS with 15+ years industry/academic/research experience

Tools

RDKit

OpenEye

Python

PyTorch

scikit-learn

Claude Code

Job description

Lilly is seeking an expert computational chemist to advance hit-to-lead programs using state‑of‑the‑art virtual screening, AI/ML, and cheminformatics. You will partner with LSMD and ExploR&D to deliver data‑driven designs and robust models that accelerate biotech collaborations.

The role emphasizes leadership, cross‑functional teamwork, and a hands‑on approach to rapidly adapt to diverse targets while advancing novel therapeutics across multiple modalities.