About the position
As a fellow you will join our faculty in the Department of Biostatistics, providing statistical support and developing innovative biostatistical methods for research projects at the cutting edge of biomedical research. You will benefit from access to unique datasets and expertise, a top-ranked scientific environment, and superb benefits, mentoring, and professional development. St. Jude is seeking an outstanding candidate for a postdoctoral fellow in multi-omics research. As a fellow you will join a group in the Department of Biostatistics, developing novel methods for the cutting-edge omics data: single cell or spatial multi-omics, cell free DNA methylation, longitudinal omics. You will benefit from access to unique datasets and expertise; top-ranked scientific environment; and superb compensation, benefits, mentoring, and professional development. One institution-funded position is available with an initial appointment of two years and a possible extension for the third year based on performance. The most recent methodological research of the group includes algorithms for cell type deconvolution, high-resolution purification, and integration of single cell multi-omics data. This postdoctoral fellow will develop innovative and generalizable methods and tools that can be applied to the in-house molecular data in pediatric cancers, such as pediatric CNS tumors and leukemias. St. Jude leads the largest pediatric cancer genome database (St. Jude Cloud) and pediatric neuro-oncology data portal, as well as two of the world's largest pediatric survivorship studies. St. Jude offers highly competitive stipends and benefits and fosters professional development.
Responsibilities
- Provide statistical support for research projects in the Department of Biostatistics.
- Develop innovative biostatistical methods for multi-omics research.
- Work with unique datasets related to pediatric cancers.
- Develop novel methods for single cell or spatial multi-omics, cell free DNA methylation, and longitudinal omics.
- Contribute to the methodological research of the group, including algorithms for cell type deconvolution and integration of single cell multi-omics data.
Requirements
- Ph.D. in biostatistics, statistics, bioinformatics, computational biology, or computer science.
- Excellent written and verbal communication skills.
- Strong computational background with programming and visualization skills in R and Python.
Nice-to-haves
- Programming skills in C or C++.
- Background in statistical genomics.
- Experience with longitudinal modeling.
- Knowledge of non-parametric statistics.
- Familiarity with machine learning and deep learning.
Benefits
- Access to unique datasets and expertise.
- Top-ranked scientific environment.
- Superb compensation and benefits.
- Mentoring and professional development opportunities.
