Director - Multi-Physics, Scale and Fidelity Predictive Modeling

Eli Lilly and Company • Indianapolis, IN

21h • Onsite

About The Position

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 At Lilly, we serve an extraordinary purpose. We make a difference for people around the globe by discovering, developing and delivering medicines that help them live longer, healthier, more active lives. Not only do we deliver breakthrough medications, but you also can count on us to develop creative solutions to support communities through philanthropy and volunteerism. Position Overview: Delivery, Device, and Connected Solutions (DDCS) sits within Eli Lilly’s Product Research & Development organization. We are a diverse team of scientists and engineers responsible for discovering, designing, and developing patient-centric drug delivery solutions across a broad range of modalities—from injection devices to novel routes of administration and nanomedicines. DDCS drives the drug delivery innovation agenda across early and late development to meet the needs of an expanding portfolio that spans small molecules, biologics, and nucleic acid therapeutics. We are seeking a collaborative, visionary computational scientist to lead the Modeling & Simulation team within DDCS. This leader will advance predictive modeling capabilities across molecular-to-system scales and single-to-multi-physics domains, integrating scientific machine learning (SciML) and AI to accelerate design, de-risk development, and deepen mechanistic understanding for drug delivery systems. This is a hands-on technical leadership role that combines strategy development, capability building, and model delivery to inform decisions—from molecular interactions and material behavior to fluid/solid mechanics, device performance, and patient-use conditions.

Requirements

• PhD in computational physics/biophysics/biomechanics, chemistry or a related engineering discipline, and 10+ years of relevant experience.
• Expert-level proficiency in theory and application in at least one of the following: molecular dynamics (MD), computational fluid dynamics (CFD), or finite element analysis (FEA), AND foundational knowledge or practical exposure to others—including validation and deployment on complex, real-world systems.
• Demonstrated experience applying physics-based methods across scales, from molecular to continuum.
• Excellent communication (visualization, scientific storytelling) and a strong record of peer-reviewed publications and conference presentations.
• A growth mindset with a passion for learning, emerging technologies, and working across disciplines.

Nice To Haves

• Proficiency with high-performance computing (e.g., MPI, GPU/CUDA, job schedulers, profiling/optimization).
• Organization and prioritization skills for fast-paced, multi-program environments, with a comfort level in ambiguity and risk.
• Breadth across methods such as: Statistical mechanics, continuum mechanics, multiscale/multiphysics coupling, coarse-graining, particle/DEM, lattice-Boltzmann, non-Newtonian fluids, contact mechanics, heat/mass transfer, electrostatics, diffusion-reaction, and materials modeling; Scientific Machine Learning / Physics-ML: PINNs, operator learning (e.g., DeepONets, FNOs, GNOs), multifidelity surrogates, Gaussian processes, active learning, and Bayesian UQ/calibration for parameter inference and decision support.
• Experience with ASME V&V 40 and model risk classification; familiarity with verification, validation, and regulatory submissions for modeling evidence.
• Hands-on with common tools (illustrative, not prescriptive): MD: LAMMPS, GROMACS, OpenMM; coarse-grain methods (Martini, SDK); CFD: OpenFOAM, Ansys Fluent/CFX, STAR-CCM+; FEA/Multiphysics: Abaqus, COMSOL, Ansys Mechanical; Workflow/Compute: Python, C/C++, MATLAB, Julia; CUDA/OpenMP; Slurm; Azure/AWS; Git, containers, CI/CD; Data/ML: NumPy/Pandas, PyTorch/TensorFlow/JAX, scikit-learn; MLflow, DVC.
• Evidence of linking modeling to business value—portfolio decisions, design tradeoffs, robustness/DFM, cost/schedule risk reductions.

Responsibilities

• Lead & Grow a High-Impact Team: Build and lead a multidisciplinary team spanning molecular dynamics (all-atom and coarse-grained), computational fluid dynamics (CFD), finite element analysis (FEA), multiscale/multiphysics coupling, uncertainty quantification (UQ), and surrogate/multifidelity modeling.
• Deliver Actionable Predictive Models: Develop and deploy models that elucidate governing physics, quantify risk, and inform device architectures, formulation strategies, and delivery system designs across the R&D lifecycle.
• Advance State-of-the-Art Capabilities: Establish a technology roadmap for digital twins, reduced-order models, operator learning/PINNs, Bayesian calibration, and MDO (multidisciplinary design optimization); drive continuous improvement in accuracy, speed, and robustness.
• Integrate SciML/AI with Physics: Combine physics-based simulation with scientific ML/AI to build hybrid models and multifidelity frameworks that accelerate exploration, optimization, and decision-making.
• Scale Modeling on Modern Compute: Leverage HPC/GPU clusters and cloud to run, manage, and govern large-scale simulations; champion software engineering best practices (version control, CI/CD, testing, reproducibility).
• Embed Modeling in the Business: Partner with engineering, device design, materials, formulation, human factors, clinical, and quality to ensure modeling is tightly coupled to program milestones, risk assessments, and regulatory strategy.
• Mentor & Raise the Bar: Set the tone for technical excellence, curiosity, and continuous improvement; mentor, develop, and grow early-career scientists and engineers.
• Drive External Leadership: Publish, present, and shape the external agenda through collaborations; identify opportunities that amplify internal capabilities and impact.

Benefits

• employees also will be eligible for a company bonus (depending, in part, on company and individual performance)
• 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).

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Education Level: Ph.D. or professional degree