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POSTDOCTORAL RESEARCHER-HDSB-Xiao Lab

UT Southwestern Medical Center
UT Southwestern Medical Center Salary
Dallas, TX Full Time
POSTED ON 4/6/2026
AVAILABLE BEFORE 6/6/2026

A postdoctoral fellow position in AI and Data Science is now available in the laboratories of Dr. Guanghua Xiao at the Quantitative Biomedical Research Center in the Peter O’Donnell School of Public Health at UT Southwestern Medical Center at UT Southwestern Medical Center at Dallas.

The Quantitative Biomedical Research Center (QBRC) is a well-established interdisciplinary research center at UT Southwestern that brings together experts in artificial intelligence, machine learning, predictive modeling, clinical informatics, digital pathology, and biomedical data science. Our goal is to develop cutting-edge computational methods and tools that enable novel discoveries and support data-driven decision-making in health care and public health.

We are seeking highly motivated, creative, and collaborative postdoctoral candidates to join our dynamic team and contribute to a portfolio of research projects applying AI and data science to real-world health care and public health data. The main research areas include:

        Electronic Health Records (EHR)

        Medical imaging (e.g., radiology and pathology)

        Real-time monitoring and wearable sensor data

The successful candidate will have the opportunity to lead and contribute to innovative projects in clinical prediction modeling, disease progression modeling, population health surveillance, and digital biomarker discovery. Our center also supports strong collaborations with clinicians, data scientists, and public health researchers.

Qualifications:

        Ph.D. in Computer Science, Statistics, Biomedical Informatics, Engineering, or a related field.

        Strong programming skills and experience with machine learning, deep learning, or AI applications.

        Interest or experience in working with large-scale health-related datasets.

Qualifications:

        Ph.D. in Computer Science, Statistics, Biomedical Informatics, Engineering, or a related field.

        Strong programming skills and experience with machine learning, deep learning, or AI applications.

        Interest or experience in working with large-scale health-related datasets.

 

Application materials must be submitted through Interfolio.

Interested individuals must upload a CV, cover letter, and a list of three references.

UT Southwestern Medical Center is committed to an educational and working environment that provides equal opportunity to all members of the University community.  As an equal opportunity employer, UT Southwestern prohibits unlawful discrimination, including discrimination on the basis of race, color, religion, national origin, sex, sexual orientation, gender identity, gender expression, age, disability, genetic information, citizenship status, or veteran status.

 

This position is security-sensitive and subject to Texas Education Code 51.215, which authorizes UT Southwestern to obtain criminal history record information.

 

Appointment rank will be commensurate with academic accomplishment and experience. Consideration may be given to applicants seeking less than a full-time schedule.

 

To learn more about the benefits UT Southwestern offers, visit https://www.utsouthwestern.edu/employees/hr-resources/

 

Benefits

    UT Southwestern is proud to offer a competitive and comprehensive benefits package to eligible employees. Our benefits are designed to support your overall wellbeing, and include:
    • PPO medical plan, available day one at no cost for full-time employee-only coverage
    • 100% coverage for preventive healthcare – no copay
    • Paid Time Off, available day one
    • Retirement Programs through the Teacher Retirement System of Texas (TRS)
    • Paid Parental Leave Benefit
    • Wellness programs
    • Tuition Reimbursement
    • Public Service Loan Forgiveness (PSLF) Qualified Employer
    • Learn more about these and other UTSW employee benefits!

Salary : $1,000 - $1,000,000

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