Postdoc Research Assoc-Causal Foundation Models for Multimodal Precision Treatment-Response Disc.

Purdue University

West Lafayette (IN)

On-site

USD 52,000 - 78,000

Full time

8 days ago

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Job summary

Purdue University invites applications for a Postdoctoral Research Associate position focused on causal foundation models for multimodal precision treatment-response discovery. The project integrates EHR trajectories, molecular profiles, and wearable sensor data to estimate treatment effects and heterogeneity in responses.

The fellow will combine representation learning, causal inference, and longitudinal modeling, guided by cross-disciplinary mentors.

Qualifications

  • PhD in relevant field; completion by start date.
  • Strong quantitative and computational skills in causal inference or ML.
  • Experience with modern ML frameworks and scientific communication.

Responsibilities

  • Develop and evaluate methods combining multimodal representation learning and causal treatment-effect estimation.
  • Analyze biomedical data; assess transferability, uncertainty, and subgroup responses.
  • Lead manuscripts, contribute to proposals, and collaborate across engineering, data science, and health sciences.

Skills

Causal inference
Machine learning
Multimodal learning
Longitudinal modeling
Optimization
Biomedical data analytics
Python

Education

PhD in operations research/industrial or biomedical engineering/biomedical informatics/computer science

Tools

Python

Job description

Postdoc Research Assoc-Causal Foundation Models for Multimodal Precision Treatment-Response Disc.

Req Id: 44671

Job Title: Postdoc Research Assoc-Causal Foundation Models for Multimodal Precision Treatment-Response Disc.

City: West Lafayette

FLSA Status

Exempt

Job Summary

Applications are invited for a Postdoctoral Research Associate position at Purdue University, co-mentored by Nan Kong, PhD (Biomedical Engineering and Industrial Engineering), and Serena Guo, MD, PhD (Pharmacy Practice). The project will develop a causal multimodal foundation model integrating electronic health record (EHR) trajectories, molecular profiles, and longitudinal wearable/mobile sensor data to estimate treatment effects and identify heterogeneous treatment responses.

The fellow will combine representation learning, causal inference, longitudinal modeling, and operations research, with interdisciplinary mentorship and professional development to support an independent academic career.

Research Areas

The fellow will contribute to the following interconnected areas:

  • Multimodal foundation models and transferable patient representations across temporal scales, missingness patterns, and measurement processes
  • Causal inference for longitudinal treatment effects, addressing confounding and clinical treatment selection
  • Treatment-response heterogeneity and operations research methods for individualized treatment decision-making
Primary Responsibilities
  • Develop and evaluate new methods combining multimodal representation learning and causal treatment-effect estimation.
  • Integrate and analyze biomedical data; assess model transferability, uncertainty, and subgroup treatment responses.
  • Lead manuscripts, contribute to grant proposals and reproducible research tools, and collaborate across engineering, data science, and health sciences.
Core Qualifications
  1. PhD in operations research, industrial or biomedical engineering, biomedical/health informatics, computer science, statistics, biostatistics, computational biology, or a related field. Candidates nearing completion of their doctorate are welcome to apply; the degree must be completed by the appointment start date.
  2. Strong quantitative and computational skills, with experience in one or more of causal inference, machine learning/foundation models, multimodal learning, longitudinal modeling, optimization, or biomedical data analytics.
  3. Demonstrated methodological research ability, scholarly productivity, and strong communication and collaboration skills. Python proficiency and experience with modern machine-learning frameworks are desirable.
Additional Fellowship Opportunity

Applicants are also encouraged to apply for Purdue’s Lillian Gilbreth Postdoctoral Fellowships , which offer interdisciplinary research training and professional development for academic careers. Fellowship awards are subject to program eligibility and competitive selection. The applicant link is towards the bottom of the website. To be considered for this fellowship, please submit your application by October 16, 2026.

Application Materials

Curriculum vitae; cover letter describing research interests, relevant methodological and computational experience, and career goals; and contact information for three references. General postdoctoral applications are separate from the Gilbreth Fellowship application process.

Co-Mentors/Application Contacts

Nan Kong, PhD — Professor of Biomedical Engineering and Industrial Engineering; nkong@purdue.edu

Jingchuan Serena Guo, MD, PhD — Associate Professor of Pharmacy Practice; serena.guo@purdue.edu

Purdue University is an equal opportunity/equal access university.

Posting Start Date: 10/16/26

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