Assistant Scientist - AI-Enabled Immune Digital Twin Workflows, Data Assimilation, and Ensemble

Indiana University Bloomington; Bloomington (IN); On-site; USD 85,000 - 115,000; Full time

Job summary

Indiana University Bloomington is seeking an Assistant Scientist to develop AI-enabled immune digital twin workflows with data assimilation and ensemble updating. The role focuses on reproducible Python-based pipelines, Kalman/Bayesian updating, and anomaly detection, under Dr. James A. Glazier’s direction.

The position involves software engineering, CI/CD, containerization, and integration with external platforms like Vivarium and QSP, with collaboration across national consortium partners.

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.
• One year of successful postdoctoral research experience.

Responsibilities

• Build reproducible, testable sequential data-assimilating digital twin workflows under senior supervision.
• Develop patient-specific forecasting and rebasing pipelines; design anomaly detection and residual-monitoring logic.
• Coordinate software integration, CI/CD, containers, and ensemble interfaces with national consortium platforms.

Skills

Python

Julia

R

MATLAB

Data assimilation

Mechanistic modeling

QSP

Vivarium

Education

Ph.D. or equivalent terminal degree

Tools

CI/CD

Containers

Job description

Posting Details

Title

Assistant Scientist - AI-Enabled Immune Digital Twin Workflows,Data Assimilation, and Ensemble Updating

Appointment Status

Non-Tenure Track

Department

IU Bloomington Intelligent Systems Engineering

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.
• One year of successful postdoctoral research experience.

Department Contact for Questions

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

Salary and Rank

100,000/Assistant Scientist

For Best Consideration Date

11/02/2026

Posting Number

IU-101733-2026