Postdoctoral Biostatistics & Spatial Omics Scientist

Memorial Sloan Kettering Cancer Center; New York (NY); On-site; USD 72,000 - 88,000; Full time

Job summary

Memorial Sloan Kettering Cancer Center (MSK) invites applications for a PhD-level Computational Scientist to lead cutting-edge translational cancer research. The role merges rigorous statistics with single-cell and spatial omics, guiding the tumor immune microenvironment analysis and enabling clinical translation in surgical oncology.

You will collaborate with computational biologists, statisticians, and surgeons to develop novel methodologies, apply them to hs-scRNA/Spatial data, and contribute

Qualifications

• PhD in Biostatistics, Statistics, Computational Biology, Bioinformatics, or related quantitative field.
• Experience analyzing paired single-cell RNA-seq and V(D)J/TCR sequencing datasets.
• Ability to translate complex mathematical theory to clinical interpretation.
• Outstanding communication and collaboration across multidisciplinary teams.

Responsibilities

• Develop, refine, and apply statistical methods for high-dimensional spatial omics and single-cell data.
• Map tumor immune microenvironment (TIME) and identify niche architectures.
• Collaborate with computational biologists, statisticians, and surgeons to translate findings.
• Provide expert guidance on study design, power calculations, and grant support.

Skills

Single-cell analysis

Spatial omics

Python & R

Biostatistics

Communication skills

Education

PhD in Biostatistics or related field

Tools

Imaging Mass Cytometry (IMC)

10x Genomics Xenium

NanoString CosMx

10x Genomics Visium

Seurat

Giotto

Bioconductor

Job description

Memorial Sloan Kettering Cancer Center (MSK) invites applications for a PhD-level Computational Scientist to lead cutting-edge translational cancer research. The role merges rigorous statistics with single-cell and spatial omics, guiding the tumor immune microenvironment analysis and enabling clinical translation in surgical oncology.

You will collaborate with computational biologists, statisticians, and surgeons to develop novel methodologies, apply them to hs-scRNA/Spatial data, and contribute