POSTDOCTORAL ASSOCIATE

Duke Careers • Durham, NC

1d

About The Position

Established in 1930, Duke University School of Medicine is the youngest of the nation's top medical schools. Ranked sixth among medical schools in the nation, the School takes pride in being an inclusive community of outstanding learners, investigators, clinicians, and staff where interdisciplinary collaboration is embraced and great ideas accelerate translation of fundamental scientific discoveries to improve human health locally and around the globe. Composed of more than 2,500 faculty physicians and researchers, more than 1,300 students, and more than 6,000 staff, the Duke University School of Medicine along with the Duke University School of Nursing, Duke University Health System and the Private Diagnostic Clinic (PDC) comprise Duke Health. a world-class academic medical center. The Health System encompasses Duke University Hospital, Duke Regional Hospital, Duke Raleigh Hospital, Duke Primary Care, Duke Home and Hospice, Duke Health and Wellness, and multiple affiliations.
The Department of Biostatistics & Bioinformatics (B&B) at the Duke University School of Medicine engages in methodological and collaborative research, providing international and regional leadership in biostatistics, genomics, biomedical informatics, artificial intelligence and health data science. The Postdoctoral Associate will conduct research in statistical machine learning and biomedical data science, developing new methodology and scalable algorithms, and collaborating with interdisciplinary teams at Duke.

Requirements

• Ph.D. in Statistics/Biostatistics/Computer Science/Applied Math (or related) by start date.
• Strong research background in statistical learning/high-dimensional inference.
• Proficiency in scientific computing (e.g., Python/R) and evidence of research productivity.

Nice To Haves

• Experience with modern ML and/or biomedical data (e.g., EHR), optimization, or tensor methods.

Responsibilities

• Develop statistical/ML methods and theory for high-dimensional and structured data.
• Implement and evaluate algorithms; maintain reproducible code and documentation.
• Analyze biomedical/health datasets (e.g., electronic health records) in collaborative projects.
• Publish in leading venues and present results at seminars/conferences.
• Participate in group meetings and contribute to mentoring/coordination as appropriate.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree