Postdoctoral Associate - Health Data Science

Company: University Of Minnesota

Location: Minneapolis, MN

Posted on: October 21

University Description

The University of Minnesota is a top-tier R1 public research university, recognized globally for its academic excellence and research impact. Ranked 63th in the U.S. News & World Report 2024 Best Global Universities, the university is a leader in numerous disciplines, including health and medical sciences. The University of Minnesota Medical School is ranked among the top 30 in the United States for its research performance, underscoring its commitment to advancing medical innovation and healthcare solutions.

Role Description

The University of Minnesota Medical School is seeking a highly motivated Postdoctoral Associate specializing in data science. The successful candidate will work with large, real-world datasets encompassing over 1 million patients from tertiary hospitals and acute care settings. The research involves developing and applying cutting-edge, trustworthy machine learning (ML) and artificial intelligence (AI) solutions to address significant healthcare challenges. This position provides a unique opportunity to leverage big data from multimodal sourcesincluding electronic health records (EHR), clinical notes, medical signals, and multi-omics datato drive impactful research that directly contributes to real-world healthcare improvements.

Qualification

• PhD or MD in a relevant field (e.g., biomedical informatics, data science, biostatistics, or health/medical sciences).
• A strong record of publications in peer-reviewed journals.
• Extensive hands-on experience with data analysis and programming, particularly with R/Python, and familiarity with modern AI/ML platforms and data science libraries.

Application information

• To be considered for this position, please submit your full Curriculum Vitae (CV) and highlight your motivation for applying and why you are interested in this opportunity.
• Questions can be directed to [email protected]
• For more information about PI and ongoing research, please visit: https://fengx13.github.io/
• We strongly encourage applicants from groups traditionally underrepresented in the research field to apply.
• Please note that the review process may take time, and only short-listed candidates will be contacted for further steps.
• Visa sponsorship will be provided for qualified international candidates