Postdoctoral Research Position in Health Data Exploration & Analytics Lab (HEAL)

Description

The Health Data Exploration & Analytics Lab (HEAL) at the Lucy Family Institute for Data and Society seeks highly motivated and enthusiastic candidates to fill a post-doctoral research fellow or a research faculty position at the intersection of data science, AI, and health. The candidate with work with Dr. Fang Liu, Director of HEAL (https://lucyinstitute.nd.edu/centers-and-labs/health-data-exploration-analytics-lab/) and Notre Dame Collegiate Professor in the Department of Applied and Computational Mathematics and Statistics at Notre Dame (https://acms.nd.edu/people/fang-liu/ ), as well as other faculty and staff at the Institute and industry partners. This position presents unique opportunities to gain research experience, professional development, and work on project with a dynamic interdisciplinary team.

Responsibilities
The successful candidate will focus on the development and application of novel AI, machine learning, and statistical methods for biomedical and health data. The candidate will engage in both independent and collaborative research, driving innovative projects at the intersection of AI, machine learning, statistics, and biomedical sciences. 

 

Job responsibilities may include: develop novel machine learning and statistical methods for large-scale real-world health and biomedical data, interpret results, and produce real-world evidence for critical decision making; collaborate with faculty, research staff and students, and domain experts.  Present in academic conferences and lead or contribute to manuscript publications in high-impact journals; lead or assist in the grant applications and reports for ongoing funded projects; help organize workshops or conferences on AI and health data.

Qualifications

A Ph.D. in statistics, computer science, biostatistics, mathematics, or a closely related discipline must be conferred by the time the position begins. Strong technical foundation in statistical modeling, machine learning, or AI; Proficiency in computing and programming; excellent communication and collaborative skills. A record of strong publications in peer-reviewed journals or conference proceedings is preferable. 

We will begin reviewing completed applications on Sep 30, 2025 until the position is filled.  Position can start immediately and no later than Jan 15, 2026. The position is funded for a year with a possibility for an extension for another year, depending on performance. Salary will commensurate with skills and experience, and the position is benefit-eligible.

 

Questions about the positions may be addressed to Dr. Fang Liu at fliu2@nd.edu.

 

 

About Lucy Family Institute for Data and Society
To find out more about the Lucy Institute for Data & Society, please refer to https://lucyinstitute.nd.edu/ and the Institute's most recent annual report https://online.flippingbook.com/view/68511823/

Application Instructions

 

Applications, including a cover letter, curriculum vitae, research statement should be submitted through the Interfolio system. Applicants should also arrange for at least three letters of recommendation to be submitted via Interfolio.

Equal Employment Opportunity Statement

The University of Notre Dame seeks to attract, develop, and retain the highest quality faculty, staff and administration. The University is an Equal Opportunity Employer, and does not discriminate on the basis of race, color, national or ethnic origin, sex, disability, veteran status, genetic information, or age in employment. Moreover, Notre Dame prohibits discrimination against veterans or disabled qualified individuals, and complies with 41 CFR 60-741.5(a) and 41 CFR 60-300.5(a). We strongly encourage applications from candidates attracted to a university with a Catholic identity.

Background Check 

This appointment is contingent upon the successful completion of a background check. Applicants will be asked to identify all felony convictions and/or pending felony charges. Felony convictions do not automatically bar an individual from employment. Each case will be examined separately to determine the appropriateness of employment in the particular position. Failure to be forthcoming or dishonesty with respect to felony disclosures can result i