AI PhD Causal Machine Learning and Digital Twins Internship

About the role

This 12‑week summer internship in Lilly’s Advanced Intelligence & Research organization focuses on causal machine learning and digital twins for clinical development. You will work on a scoped project with real business impact, collaborating with research scientists and clinical partners.

Key responsibilities

• Develop and apply causal inference methods (e.g., causal graphs, propensity scoring, instrumental variables, difference‑in‑differences) to estimate treatment effects.
• Design and build digital twins of patients, disease trajectories, or clinical trials using mechanistic, statistical, or generative modeling approaches.
• Validate and calibrate digital twins against clinical and real‑world data.
• Partner with clinical and scientific collaborators to frame questions, communicate insights, and support decision‑making.
• Stay current with methodological advances and justify method selection.

Required profile

• Currently enrolled in a PhD program in Statistics, Biostatistics, Computer Science, Computational Biology, Operations Research, Mathematics/Applied Math, or a related quantitative field.
• Foundational knowledge of causal inference or statistical modeling and hands‑on programming experience in Python.
• Authorized to work in the United States on a full‑time basis without sponsorship.

Required skills

• Python programming (and/or R).
• Deep knowledge of causal inference frameworks (potential outcomes, DAGs, structural causal models, propensity scores, instrumental variables, difference‑in‑differences).
• Experience building digital twins or simulation models (mechanistic, statistical, agent‑based, Bayesian).
• Familiarity with clinical, real‑world, or observational healthcare data.
• Strong communication skills to translate methodological choices for clinical and business stakeholders.

What we offer

• Competitive salary and free parking.
• Access to Lilly’s LIFE fitness center, bike garage, and employee discounts.
• Subsidized housing if relocation is required.
• Professional development activities, mentoring, and a final presentation to senior leaders.
• One week of paid time off during the summer shutdown (July 5‑9).