Postdoctoral Fellow - AI-Enabled Immune Digital Twin Workflows, Data Assimilation, and Ensemble Updating

Indiana University; Bloomington (IN); On-site; USD 63,000 - 77,000; Full time

Job summary

Indiana University in Bloomington seeks a Postdoctoral Fellow to lead AI-enabled immune digital twin workflows, data assimilation, and ensemble updating. You will build reproducible Python workflows, implement forecasting methods, and coordinate complex model ensembles with national consortium partners.

The role combines software engineering with quantitative biology, requiring a Ph.D. in a quantitative, computational, or biomedical field and proficiency in Python, Julia, R, or MATLAB.

Qualifications

• Ph.D. or equivalent terminal degree in quantitative, computational, or biomedical discipline.
• Programming proficiency in Python, Julia, R, or MATLAB; background in mechanistic modeling (ODE/dynamical systems, QSP, or agent-based).
• Familiarity with inflammation, cytokine signaling, sepsis, or critical care biology.

Responsibilities

• Develop Python workflows for short-horizon forecasting and patient-specific rebasing; implement data-assimilation methods (Kalman/Bayesian updating); design anomaly detection and missing-information inference logic.
• Build reproducible computational packages (CI/CD, containers, testing); manage ensemble interfaces; integrate workflows with external consortium platforms (Vivarium, QSP); write technical publications.

Skills

Python

Julia

R

MATLAB

Data assimilation

Kalman updating

Bayesian updating

Mechanistic modeling

Agent-based modeling

Inflammation biology

Education

Ph.D. or equivalent terminal degree in quantitative, computational, or biomedical discipline

Tools

Vivarium

QSP

Job description

Postdoctoral Fellow - AI-Enabled Immune Digital Twin Workflows, Data Assimilation, and Ensemble Updating

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Title Postdoctoral Fellow - AI-Enabled Immune Digital Twin Workflows, Data Assimilation, and Ensemble Updating

Appointment Status

Department

Location

Location Bloomington

Position Summary

Your primary duties will be to build reproducible, testable, sequential data-assimilating digital twin workflows under the direction of Dr. James A. Glazier. You will implement patient-specific forecasting and rebasing pipelines, design anomaly-detection and residual-monitoring logic, infer unobserved state parameters, manage complex model ensemble interfaces, and coordinate computational infrastructure with national consortium collaborators.

60% Digital Twin Workflows & Data Assimilation: Develop Python workflows for short-horizon forecasting and patient-specific rebasing; implement data-assimilation methods (Kalman/Bayesian updating); design anomaly detection and missing-information inference logic.

40% Software Engineering & Integration: Build reproducible computational packages(CI/CD, containers, testing); manage ensemble interfaces; integrate workflows with external consortium platforms (Vivarium, QSP ); write technical publications.

Basic Qualifications

Ph.D. or equivalent terminal degree in quantitative, computational, or biomedical discipline.

Programming proficiency in Python, Julia, R, or MATLAB ; background in mechanistic modeling ( ODE /dynamical systems, QSP , or agent-based); familiarity with inflammation, cytokine signaling, sepsis, or critical care biology.

Department Contact for Questions

Please contact Professor James Glazier at [e-mail] with questions about the position.

Additional Qualifications

Salary and Rank

Salary and Rank 70,000/Postdoctoral Fellow

Special Instructions

For Best Consideration Date

For Best Consideration Date 11/02/2026

Expected Start Date

Posting Number

Supplemental Questions

Required fields are indicated with an asterisk (*).

• * Have you previously been employed with IU?
  • Yes
  • No