The University of South Carolina (USC) is a leading public research university, and the Arnold School of Public Health (ASPH) is consistently ranked among the top public health schools in the nation. The Division of Biostatistics, within the Department of Epidemiology and Biostatistics at ASPH, is home to a growing group of faculty working on modern statistical methodology and its applications to public health, wearable and digital biomarker data, neuroimaging, and aging research. The division fosters close collaboration across biostatistics, epidemiology, and clinical investigator teams, and offers a supportive, collegial environment for postdoctoral training.
The Division of Biostatistics at the University of South Carolina invites applications for a Biostatistics Postdoctoral Fellow position. The postdoc will be housed at University of South Carolina. The postdoc will work under the direct supervision of Dr. Rahul Ghosal, and co-supervised by Dr. Erjia Cui from University of Minnesota. The postdoc will carry out research at the intersection of functional data analysis and distributional data analysis, with applications to wearable and digital health data. While regular mentorship and guidance will be provided to support professional growth, the scholar is expected to exercise independent judgment in prioritizing tasks, selecting appropriate analytical approaches, and resolving challenges encountered in day-to-day research.
This is a one-year appointment with the possibility of renewal for up to one additional year, contingent upon satisfactory performance and availability of funding.
Primary responsibilities include statistical methods development, manuscript writing, software development and knowledge dissemination.
Minimum Required Education and Experience: A Doctoral (Ph.D.) degree in Statistics or Biostatistics is required by the start date of employment.
Preferred Qualifications: A track record of methodological publications in peer-reviewed journals, strong understanding of functional data analysis, longitudinal data analysis, and related statistical concepts. Some experience analyzing wearable or digital biomarker data will be preferred. Clear communication and presentation skills are needed for engaging with faculty investigators and project teams.
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