Associate Scientist: Single-Cell Genomics & Multi-Omics

Mount Sinai Morningside; New York (NY); On-site; USD 59,000 - 99,000; Full time

Job summary

Mount Sinai Morningside seeks an Associate Scientist to lead and support analysis of large-scale molecular datasets in a collaborative research environment. This role focuses on single-cell transcriptomics and epigenomics, with emphasis on multi-omic technologies.

You will drive computational analyses and partner with an integrated team to derive biological insights from complex data. Applicants should have a PhD and strong programming skills in R and Python, experience with scRNA-seq, ATAC-seq,

Qualifications

• Ph.D. in Biological Science or related field; PhD in Computational Biology, Bioinformatics, Genomics, Statistics, Computer Science, or related field highly preferred
• Three years' experience
• Strong experience analyzing bulk and single-cell RNA-seq and epigenomic data
• Proficiency in R, including common single-cell analysis frameworks
• Experience working with large-scale genomic datasets and high-performance computing environments
• Strong statistical background and data visualization skills
• Experience analyzing DNA methylation data (e.g., array-based or sequencing-based approaches)
• Experience analyzing long-read RNA sequencing datasets
• Demonstrated use of machine learning/AI methods for genomic data integration or prediction
• Familiarity with cloud-based workflows and reproducible pipeline development
• Track record of publications in peer-reviewed journals

Responsibilities

• Lead analysis of single-cell RNA-seq and multiome datasets (joint RNA/ATAC profiling)
• Perform integrative analysis across modalities, including bulk RNA-seq, ATAC-seq, and DNA methylation datasets
• Develop processing pipelines for novel single cell multiomic technologies
• Apply statistical modeling and machine learning methods to identify cellular states, regulatory programs, and epigenetic signatures
• Design and implement integrative multi-omic analyses across cohorts and experimental systems
• Present findings internally and contribute to publications and grant applications
• Stay current with emerging single-cell and AI-driven genomic analysis methodologies
• Performs other related duties.

Skills

Single-cell transcriptomics

Epigenomics

R programming

Large-scale genomics data

Machine learning

Cloud workflows

Publications track record

Statistics

High-performance computing

Data visualization

Education

PhD in Biological Science

PhD in Computational Biology

Tools

R

Python

HPC

Scikit-learn

Job description

Mount Sinai Morningside seeks an Associate Scientist to lead and support analysis of large-scale molecular datasets in a collaborative research environment. This role focuses on single-cell transcriptomics and epigenomics, with emphasis on multi-omic technologies.

You will drive computational analyses and partner with an integrated team to derive biological insights from complex data. Applicants should have a PhD and strong programming skills in R and Python, experience with scRNA-seq, ATAC-seq,