Postdoc: Computational Biostatistics & Spatial Omics Scientist

msk; New York (NY); On-site; USD 72,000 - 88,000; Full time

Benefits offered by this job

Competitive salary

Benefits package

Collaborative environment

Job summary

Memorial Sloan Kettering Cancer Center (MSK) in New York seeks a PhD-level Computational Scientist to lead translational cancer research at the intersection of statistics and spatial omics. You will map the tumor immune microenvironment, decode cellular niches, and collaborate with clinicians, biologists, and surgeons.

You will develop statistical methods, apply them to single-cell RNA-seq and spatial profiling data, and contribute to study design and grant proposals.

Qualifications

• PhD in Biostatistics, Statistics, Computational Biology, Bioinformatics, or closely related quantitative field with strong core statistical training.
• Proven track record in analyzing and modeling single-cell and high-plex spatial profiling data.
• Direct experience processing data from multiplexed imaging or sequencing-based spatial platforms (IMC, Xenium, CosMx, Visium).
• Advanced proficiency in Python and/or R and Bioconductor packages; experience with Seurat/Giotto.

Responsibilities

• Develop, validate, and apply novel statistical frameworks for high-dimensional spatial omics and single-cell data.
• Build scalable pipelines for multiplexed spatial imaging data and paired single-cell multi-omics.
• Collaborate with computational biologists, statisticians, and clinicians to translate findings into clinical context.

Skills

Python

R

Single-cell analysis

Spatial omics

Bioconductor

Seurat

Data visualization

Education

PhD in Biostatistics, Statistics, Computational Biology, Bioinformatics, or related field

Tools

Imaging Mass Cytometry (IMC)

10x Genomics Xenium

NanoString CosMx

10x Genomics Visium

Job description

Memorial Sloan Kettering Cancer Center (MSK) in New York seeks a PhD-level Computational Scientist to lead translational cancer research at the intersection of statistics and spatial omics. You will map the tumor immune microenvironment, decode cellular niches, and collaborate with clinicians, biologists, and surgeons.

You will develop statistical methods, apply them to single-cell RNA-seq and spatial profiling data, and contribute to study design and grant proposals.