"Staff Associate II"

Staff Associate II

Employer: Columbia University Irving Medical Center/VP&S

Location: New York City, New York (US)

Salary: $80,000-$90,000 a year

Closing date: Mar 26, 2026

Discipline: Life Sciences, Pharmacology

Position Type: Full Time

Job Type: Other

Organization Type: Academia

Job Details

The Abate-Shen Lab at Columbia University Irving Medical Center is seeking a Staff Associate II to provide computational biology and bioinformatics support for a large-scale cancer biology project involving the analysis of mouse and human tissues using single-cell genomics and other molecular profiling technologies. This role will support the development and application of platform technologies for analyzing cancer samples in collaboration with a team of investigators and researchers at Columbia University. The successful candidate must have functional knowledge of and experience working with a Linux operating system, as well as fluency in at least one programming language such as Python or R; a background in cancer biology is preferred. In this position, the Staff Associate II will work collaboratively with team members to troubleshoot computational analyses and is expected to operate with a moderate level of supervision and independent judgment. The role requires technical expertise in the bioinformatic analysis of genomic and/or transcriptomic sequencing data, along with excellent written communication skills, including the ability to clearly document data electronically and develop and maintain experimental protocols. Qualified candidates should hold a Bachelor’s degree in biology, chemistry, physics, mathematics, engineering, bioinformatics, computer science, or a related field, along with at least two years of relevant experience, or a Master’s degree in a related discipline. Experience with bioinformatic analysis of genomic and/or transcriptomic sequencing data, working in a Linux environment, and proficiency in a high-level programming language such as Python or R is required, and a basic knowledge of cancer biology is strongly preferred.

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