Postdoctoral Research Associate - Biostatistics

St. Jude Children's Research Hospital•Memphis, TN

55d

About The Position

A postdoctoral research associate position is available in the Department of Biostatistics. As a fellow, you will join our faculty in the Department of Biostatistics and work closely with biostatistics faculty collaborating with the Childhood Cancer Survivorship Program (CCSP). You will develop innovative biostatistical methods for childhood cancer survivorship research and collaborate with CCSP investigators. Biostatistics methods will include complex survival analysis, longitudinal analysis, machine learning, and causal inference. You will benefit from access to unique datasets and expertise from two of the world’s largest pediatric survivorship studies, St. Jude Lifetime Cohort Study (SJLIFE) and the Childhood Cancer Survivor Study (CCSS), a top-ranked scientific environment, and superb benefits, mentoring, and professional development. St. Jude is seeking an outstanding candidate for a postdoctoral fellowship in biostatistics methods and applications involving pediatric cancer and catastrophic diseases. A position is available in survival analysis, longitudinal data analysis, causal inference and predictive modeling using machine learning methods. St. Jude leads two of the world’s largest pediatric survivorship research studies, St. Jude Lifetime Cohort Study (SJLIFE) and the Childhood Cancer Survivor Study (CCSS), and the largest pediatric cancer genome database, St. Jude Cloud.

Requirements

Ph.D. in biostatistics, statistics, or a closely related field.
Excellent communication skills.
Experience in applied or method research in survival analysis.
Strong computational background.
Demonstrate excellent written and verbal communication skills.

Responsibilities

Develop innovative biostatistical methods for childhood cancer survivorship research.
Collaborate with CCSP investigators.
Apply biostatistics methods including complex survival analysis, longitudinal analysis, machine learning, and causal inference.
Conduct research in survival analysis, longitudinal data analysis, causal inference, and predictive modeling using machine learning methods.