Overview
The Suh Laboratory at Columbia University Irving Medical Center is seeking a highly motivated postdoctoral fellow to lead bioinformatics and computational analyses in our research on human ovarian aging. This position focuses on integrating single-nuclei multi-omics (snRNA-seq, snATAC-seq) and spatial transcriptomics to characterize the molecular and genetic mechanisms driving ovarian aging.
The successful candidate will develop and apply computational pipelines to analyze high-dimensional datasets, reconstruct aging trajectories, and identify key regulatory drivers and functional non-coding variants associated with reproductive aging. The postdoc will collaborate with wet-lab researchers who will perform experimental validation and contribute to manuscripts, presentations, and grant applications. This position provides an excellent opportunity to work at the intersection of aging biology, reproductive science, and computational genomics, contributing to fundamental discoveries in women’s health and aging research.
· Analyze and integrate single-nuclei multi-omics (snRNA-seq, snATAC-seq) and spatial transcriptomics data to characterize the molecular mechanisms of ovarian aging.
· Develop and apply computational pipelines for high-dimensional data analysis, including reconstructing aging trajectories and prioritizing functional non-coding variants.
· Collaborate with wet-lab researchers to interpret findings and support experimental validation of key regulatory elements.
· Contribute to scientific communication, including manuscript preparation, presentations, and grant applications.
The Scientific Community: Situated on a 20-acre campus in Northern Manhattan CUIMC provides global leadership in scientific research, health and medical education, and patient care. CUIMC is especially proud of its relationship with the surrounding Washington Heights community and has numerous research and clinical programs in Northern Manhattan, including Harlem, Washington Heights, and Inwood. CUIMC also has more than 40 state-of-the-art shared research facilities physically housed in and administered by its departments, centers, and institutes. These resources offer the highest-quality scientific technology to the community, and many also offer education and training, as needed. We offer competitive salary and benefit packages.
Minimum Qualifications
A doctoral degree in biology, bioinformatics, computational biology, or a related field with a focus on aging, reproductive biology, or women’s health.
Strong expertise in single-cell omics analysis (snRNA-seq, snATAC-seq, and/or spatial transcriptomics).
Solid understanding of the human genome, specifically related to gene expression patterns and cell biology in the context of ovarian aging.
Proficiency in R and at least one other programming language, such as Python or Perl, with experience in handling large-scale biological datasets
Ability to work independently and collaboratively in a multidisciplinary research environment
Preferred Qualifications
Background in ovarian biology, reproductive aging, or aging biology in general.
Experience in integrative multi-omics analysis and statistical modeling of biological systems.
Strong publication record in relevant fields
The Department of Obstetrics and Gynecology is dedicated to the goal of building a multicultural faculty and staff committed to teaching, working and serving in a diverse community, and strongly encourages applications from candidates of traditionally underrepresented backgrounds.
We are continuously seeking to recruit individuals who will enhance the diversity of our workplace and the effectiveness of our organization.
Equal Employment Opportunity Statement
Columbia University is an Equal Opportunity Employer / Disability / Veteran
Pay Transparency Disclosure
The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University’s good faith and reasonable estimate of the range of possible compensation at the time of posting.
