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

Indiana University; Bloomington (IN); On-site; USD 80,000 - 110,000; Full time

Job summary

Indiana University in Bloomington seeks an Assistant Scientist to develop AI-enabled immune digital twin workflows with data assimilation, Kalman/Bayesian updating, and ensemble updating under Dr. James Glazier.

You will implement patient-specific forecasting and rebasing, design anomaly-detection and residual-monitoring logic, manage complex model ensembles, and coordinate computational infrastructure with national collaborators; publication of technical work is expected.

Qualifications

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

Responsibilities

• Build reproducible, testable, sequential data-assimilating digital twin workflows.
• Implement patient-specific forecasting and rebasing pipelines; data-assimilation (Kalman/Bayesian) methods.
• Design anomaly-detection and residual-monitoring logic; infer unobserved state parameters.
• Manage complex model ensembles and coordinate computational infrastructure with collaborators.
• Write technical publications describing methods and results.

Skills

Python

Julia

R

MATLAB

Mechanistic modeling

Inflammation biology

Education

Ph.D. or equivalent terminal degree

Tools

CI/CD

Containerization

Unit testing

Job description

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

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

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.

Supplemental Questions

Required fields are indicated with an asterisk (*).

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