Post-doctoral Computational Chemist, Advanced Molecular Design
Eli Lilly and Company
August 14, 2026
On-site
Indianapolis, IN
Clinical Research and Development
Post-Doctoral Computational Chemist (Onsite; Indianapolis, Indiana)
Responsibilities:
- Execute advanced quantum mechanical calculations, molecular dynamics simulations, and free energy calculations to study protein motion, protein-ligand interactions, and protein-protein interactions for structure-based drug design.
- Build and maintain informatic infrastructure to enable broad use of QM, MD, and free energy methods across drug discovery projects.
- Script and automate computational workflows to maximize throughput and reproducibility.
- Develop deep working knowledge of computational chemistry suites including Schrödinger, MOE, Gaussian/Orca/GAMESS, and one or more MD packages (OpenMM, AMBER, CHARMM, GROMACS, or Desmond).
- Stay current with emerging computational drug discovery methods, including AI/ML for molecular property prediction and design.
- Collaborate with multidisciplinary teams (medicinal chemists, structural biologists, biologists, statisticians, toxicologists) and communicate progress via presentations.
- Collaborate with discovery scientists to advance molecules from leads to quality drug candidates.
Basic Requirements:
- Ph.D. in Computational Chemistry, Computer Science, Cheminformatics, Bioinformatics, Biophysics, or related field (all requirements completed by Aug 2026).
- Authorized to work in the United States full-time; no visa sponsorship.
Additional Skills/Preferences:
- Theoretical physical chemistry and organic chemistry; experience with MD and QM/free-energy methods on protein-ligand systems.
- Python (and other scripting/programming); ability to work independently and collaboratively.
- Knowledge of structure-based lead optimization and AI/ML; familiarity with ADME/toxicology.
- HPC experience; cheminformatics toolkits (RDKit, OpenEye) and/or structural platforms (Schrödinger, ChemAxon).
- Scientific computing libraries/APIs (MDAnalysis, NumPy, SciPy, pandas); reproducible code and version control (GitHub/GitLab).
- Experience integrating structural biology data (cryo-EM, X-ray, NMR, or AI-predicted structures).
Additional Information:
- Fixed-term position up to 2 years with possible 2-year extension.
Responsibilities:
- Execute advanced quantum mechanical calculations, molecular dynamics simulations, and free energy calculations to study protein motion, protein-ligand interactions, and protein-protein interactions for structure-based drug design.
- Build and maintain informatic infrastructure to enable broad use of QM, MD, and free energy methods across drug discovery projects.
- Script and automate computational workflows to maximize throughput and reproducibility.
- Develop deep working knowledge of computational chemistry suites including Schrödinger, MOE, Gaussian/Orca/GAMESS, and one or more MD packages (OpenMM, AMBER, CHARMM, GROMACS, or Desmond).
- Stay current with emerging computational drug discovery methods, including AI/ML for molecular property prediction and design.
- Collaborate with multidisciplinary teams (medicinal chemists, structural biologists, biologists, statisticians, toxicologists) and communicate progress via presentations.
- Collaborate with discovery scientists to advance molecules from leads to quality drug candidates.
Basic Requirements:
- Ph.D. in Computational Chemistry, Computer Science, Cheminformatics, Bioinformatics, Biophysics, or related field (all requirements completed by Aug 2026).
- Authorized to work in the United States full-time; no visa sponsorship.
Additional Skills/Preferences:
- Theoretical physical chemistry and organic chemistry; experience with MD and QM/free-energy methods on protein-ligand systems.
- Python (and other scripting/programming); ability to work independently and collaboratively.
- Knowledge of structure-based lead optimization and AI/ML; familiarity with ADME/toxicology.
- HPC experience; cheminformatics toolkits (RDKit, OpenEye) and/or structural platforms (Schrödinger, ChemAxon).
- Scientific computing libraries/APIs (MDAnalysis, NumPy, SciPy, pandas); reproducible code and version control (GitHub/GitLab).
- Experience integrating structural biology data (cryo-EM, X-ray, NMR, or AI-predicted structures).
Additional Information:
- Fixed-term position up to 2 years with possible 2-year extension.