Senior Scientist (Computational Genomics & Large-Scale Molecular Data Analysis)(Dr Sealfon's Lab) - Neurology

Mount Sinai Health System • New York, NY

1d

About The Position

The Senior Scientist will lead computational analysis of high-dimensional datasets and partner closely with an integrated computational-experimental team to generate biological insights from complex genomic data. The role emphasizes single-cell transcriptomics and epigenomics, large-scale dataset analysis, and quantitative and programming expertise. Machine learning and AI approaches are highly desirable.

Requirements

• Ph.D. in a science or related field, such as Computational Biology, Bioinformatics, Genomics, Statistics, or Computer Science.
• At least five years of experience with scientific investigation.
• Demonstrated outstanding achievement in a field of research.
• Contributions to peer-reviewed publications, inventions, or similar work, at least some of which had a major impact on advancing the field or discipline.

Nice To Haves

• Prior experience successfully securing external grant funding.
• 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 using array-based or sequencing-based approaches.
• Experience analyzing long-read RNA sequencing datasets.
• Demonstrated use of machine learning or 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 involving joint RNA/ATAC profiling.
• Perform integrative analyses 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.
• Perform other related duties.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree