Post-doctoral Scientist - Reaction Informatics

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world.

Organization Overview

Lilly Small Molecule Discovery is an organization purpose-built to create molecules that make life better for people. We focus on using cutting edge science to unlock new approaches that can treat people suffering from diseases with poor treatment options. We continually challenge ourselves to deliver molecules that can provide breakthrough efficacy with the highest possible safety margins. We are dedicated to optimizing our mindset, technology, and processes for faster, more nimble execution. Our success is built on a culture that empowers innovative problem solving through open collaboration and individual accountability.

Discovery Technology and Platforms is a newly established function within this organization. Its mission is to accelerate molecule discovery by building highly optimized foundational platforms, streamlining lab operations through advanced technologies and data connectivity, and intentionally investing in novel technologies and capabilities.

Frontier AI is a purpose-built team that fuses scientific AI, lab automation, and unified data platforms to autonomously design, run, and refine experiments—accelerating molecule discovery.

Position Summary

Lilly is seeking a motivated and innovative Postdoctoral Scientist to develop next-generation AI models and automated pipelines for reaction prediction and condition optimization. This position offers the opportunity to work at the intersection of cheminformatics, machine learning, and automation to accelerate the Design–make–test–analyze (DMTA) cycle in small-molecule drug discovery. The successful candidate will join the Frontier AI team, a multidisciplinary team committed to advancing molecule discovery through scalable informatics platforms, predictive modeling, and high-throughput experimental integration.

Key Responsibilities 

Reaction Informatics & Predictive Modeling

• Refine deep learning models (e.g., graph-based transformers) for reaction product and condition prediction.

• Curate and integrate reaction datasets from internal sources to train and benchmark models.

• Evaluate external models (e.g., RPBP, NERF) for relevance and applicability across reaction classes.

Automation & Workflow Integration

• Develop tools and APIs to integrate predictive models with high-throughput experimentation (HTE) platforms.

• Enable data-driven reaction condition optimization and parallel library synthesis through automation-friendly workflows.

• Collaborate with the Agentic AI systems to prototype eLN-to-lab automation agents.

Cheminformatics Development

• Apply cheminformatics techniques (reaction encoding, fingerprinting, condition clustering) to support model interpretation and experimental planning.

• Partner with chemists and engineers to translate modeling outputs into actionable synthetic workflows.

Collaboration & Communication

• Work cross-functionally with medicinal chemistry, automation, and AI/ML teams.

• Present findings through internal presentations, external publications, and conferences.

Basic Qualifications

• Ph.D. in organic chemistry, cheminformatics, computational chemistry,  or related field (degree must be awarded by start date).

• Strong background in organic chemistry (particularly in synthesis or methods development), and/or mechanism and reaction modeling.

• Experience with reaction informatics and retrosynthesis algorithms.

• Proficiency in Python and one or more cheminformatics toolkits (e.g., RDKit, CGRtools).

• Experience with machine learning and deep learning frameworks (e.g., scikit-learn, PyTorch, TensorFlow).

Preferred Qualifications

• Hands-on experience with HTE platforms or automated chemistry systems.

• Familiarity with eLN systems and AI-to-lab integration.

• Demonstrated ability to work across interdisciplinary teams and contribute to tool deployment or platform development.

• Publication record in cheminformatics, reaction prediction, or automated synthesis.

Additional Information: 

• This position is not permanent. It is for a fixed duration of 2 years, with the potential to extend to a maximum of 4 years.

Physical Demands/Travel: 

• The physical demands of this job are consistent with an office and lab environment.   

• The physical demands here are representative of those that must be met by an employee to successfully perform the essential functions of this job.  

Work Environment: 

• This position’s work environment is in an office.   

• The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. 

• *To perform this job successfully, an individual must be able to perform the role and responsibilities satisfactorily. The requirements listed above are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. 

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status.

Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia Network, Black Employees at Lilly, Chinese Culture Network, Japanese International Leadership Network (JILN), Lilly India Network, Organization of Latinx at Lilly (OLA), PRIDE (LGBTQ+ Allies), Veterans Leadership Network (VLN), Women’s Initiative for Leading at Lilly (WILL), enAble (for people with disabilities). Learn more about all of our groups.

Actual compensation will depend on a candidate’s education, experience, skills, and geographic location.  The anticipated wage for this position is

Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly’s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.

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