Research Scientist - Biomolecular Simulation & Dynamics

Position Overview

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader dedicated to discovering and delivering life‐changing medicines. Lilly’s Biotechnology Discovery Research (BioTDR) organization has a strong track record in advancing novel biotherapeutic medicines into clinical research across areas of unmet medical need.

As we advance into increasingly complex modalities – including multi‐specific antibodies, conjugates, and fusion proteins – traditional static structure approaches are no longer sufficient. We are seeking a simulation expert to strengthen physics-based computational approaches for biotherapeutics discovery. In this role, you will drive all-atom and coarse-grain molecular dynamics (MD) studies to provide decision-ready insights on antibodies, multi-specifics, proteins, and conjugates, and build an integrated computational pipeline to accelerate drug discovery.

Location: Lilly Biotechnology Center, San Diego, CA
Compensation: $138,000 - $224,400

Key Responsibilities

• Run MD to assess protein stability, binding interfaces/epitopes, conformational dynamics, glycan effects, and pH/ion impacts.
• Develop and deploy coarse-grained MD workflows (e.g., MARTINI 3) to rapidly triage self-association or aggregation risk, profile membrane interactions, and characterize domain-level dynamics.
• Apply enhanced-sampling techniques to capture loop motions, macrocycle ring flips, and other rare conformational events; summarize findings with quantitative, decision-oriented metrics.
• Partner with project teams to prioritize designs and reconcile predictions with experimental data.
• Develop methods predicting MHCII-peptide registration.
• Build validated MD playbooks/SOPs (including system preparation, constant-pH/pKa workflows, force-field selection, and QC/validation) benchmarked on antibodies, multi-specifics, peptides, or macrocycles.
• Develop and apply free energy perturbation (FEP) or comparable computational methods to screen binding affinity and guide design choices.
• Publish MD-derived features (e.g., RMSF, contact persistence, hydration/SASA patches, H-bond occupancies) to the ML platform with clear data contracts.
• Provide conformational ensembles for docking rescoring and deliver structural constraints for generative design and protein-LM based optimization.

Required Qualifications

• PhD (or MS and 5+ years of experience) in Computational Biophysics, Chemistry, or related fields.

Preferred Qualifications

• 5+ years applying MD in drug/biotherapeutics discovery (in industry or in close industry-collaborative academic settings) is preferred.
• Hands-on experience with OpenMM, GROMACS, AMBER, NAMD, and PLUMED; strong analysis skills using tools such as MDAnalysis, MDTraj, or PyEMMA.
• Demonstrated expertise in coarse-grain MD (e.g., MARTINI 3) for studying aggregation, LLPS, self-association, or membrane interactions.
• Experience in modeling antibodies/biologics (including glycosylation and developability liabilities) and/or peptides/macrocycles.
• Competency with enhanced sampling techniques, uncertainty quantification, and delivering clear, decision-grade communication.
• Proficiency in Python for system preparation, workflow automation, and data analysis; comfort with Linux/HPC environments.
• Experience with physics-based free-energy methods (FEP/TI), constant-pH MD, and pKa prediction pipelines.
• Familiarity with statistical modeling and machine learning (e.g., feature engineering, simple baselines) and integrating simulation outputs into predictive models.
• Excellent communication and presentation skills with the ability to convey complex technical concepts to diverse audiences.
• Ability to work productively and collaboratively in an interdisciplinary team environment.

Benefits & Perks

• Benefits: Comprehensive benefit program including eligibility for a company-sponsored 401(k), pension, vacation, medical, dental, vision, and prescription drug benefits, as well as flexible spending accounts, life insurance, and well-being programs. Full-time equivalent employees may also be eligible for a company bonus based on performance.