Postdoctoral Research Scientist

Located in the Columbia University Medical Center in New York City, Columbia University Herbert Irving Comprehensive Cancer Center is exclusively devoted to cancer patient care, research, education, and prevention. Researchers at Herbert Irving Comprehensive Cancer Center have developed innovative procedures that have impacted cancer care in many areas, including immunologic therapy, combination therapy, chemotherapy, and radiation therapy. The multidisciplinary approach to cancer research and treatment is pioneered at our institution. The quantitative experts in the Department of Biostatistics are an integral part of and closely collaborate with clinicians, computational biologists, software engineers, and other medical professionals.

Open positions for Postdoctoral Research Scientists to develop new statistical and machine learning methods for high-dimensional and longitudinal biomedical data. Scientific questions of interest include exploring the (causal) associations between omics data, clinical variables, and disease of interest, identifying important biomarkers, or developing predictive models for disease outcomes. Possible applications include clinical studies involving microbiome data, single-cell RNA-Seq data, or spatial transcriptomics data. Responsibilities also include developing the associated software packages, assisting in the preparation of grant applications, and producing manuscripts for publication purposes. The Postdoctoral Research Scientist will work closely with Dr. Jianhua Hu in the Department of Biostatistics and possibly other faculty of Biostatistics/Statistics.

Minimum Degree Required

• Ph.D., MD, or equivalent doctoral degree in statistics/biostatistics or a related quantitative field.

Minimum Qualifications

• Candidates must have good methodology training and background in statistics/biostatistics and strong programming skills, such as R, Python, Matlab, or C, in addition to good research and data analysis experience.
• Experience and skills in machine learning methods and high dimensional "omics" data analysis are desirable.
• Ability to work independently and collaboratively