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

About the role

We are seeking a highly motivated Associate Scientist to lead and support the analysis of large-scale molecular datasets in a dynamic, collaborative research environment. This role focuses on cutting-edge functional genomics, with an emphasis on single-cell and multi-omic technologies. The Associate Scientist will drive computational analysis of high-dimensional datasets, partnering closely with a well-integrated computational-experimental team to generate biological insights from complex genomic data.

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
• Perform other related duties

Requirements

• 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

About the employer

The Mount Sinai Health System is committed to fostering an environment where everyone can contribute to excellence. We share a common dedication to delivering outstanding patient care. When you join us, you become part of Mount Sinai’s unparalleled legacy of achievement, education, and innovation as we work together to transform healthcare.

Mount Sinai Health System is one of the largest academic medical systems in the New York metro area, with more than 48,000 employees working across eight hospitals, more than 400 outpatient practices, more than 300 labs, a school of nursing, and a leading school of medicine and graduate education. Mount Sinai advances health for all people, everywhere, by taking on the most complex health care challenges of our time.

Pay

The salary range for the role is $58,661 - $98,978.78 annually. Actual salaries depend on a variety of factors, including experience, education, and operational need. The salary range does not include bonuses, incentive pay, differential pay, or other forms of compensation or benefits.