Single Cell Spatial Transcriptomics Jobs in New York

This position will serve as a senior computational scientist responsible for the analysis, integration, and interpretation of large-scale single-cell, multiomic, and genomic datasets generated by the laboratory. The individual will play a central role in transforming raw sequencing data into biologically interpretable models of human brain development and neuropsychiatric disease. The role includes end-to-end ownership of computational workflows spanning raw sequencing processing, genotype-based demultiplexing, single-cell and spatial transcriptomic analysis, and multiomic data integration. The scientist will lead the development and maintenance of reproducible analysis pipelines and will be responsible for ensuring consistency across large, heterogeneous datasets derived from multiple genetic and pharmacologic disease models. 

A major component of the position involves integrating diverse datasets-including scRNA-seq, snATAC-seq, multiome, and spatial transcriptomics-with human fetal and postmortem reference atlases to define conserved and disease-specific cell states. The individual will also contribute to the identification of regulatory programs and candidate signaling pathways for experimental validation in organoid systems. This role requires close collaboration with experimental scientists to iteratively refine hypotheses, prioritize perturbation targets, and guide experimental design based on computational findings.

https://profiles.icahn.mssm.edu/deepak-kaji 

Strength through Unity and Inclusion

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. We encourage all team members to actively participate in creating a culture that ensures fair access to opportunities, promotes inclusive practices, and supports the success of every individual.

At Mount Sinai, our leaders are committed to fostering a workplace where all employees feel valued, respected, and empowered to grow. We strive to create an environment where collaboration, fairness, and continuous learning drive positive change, improving the well-being of our staff, patients, and organization. Our leaders are expected to challenge outdated practices, promote a culture of respect, and work toward meaningful improvements that enhance patient care and workplace experiences. We are dedicated to building a supportive and welcoming environment where everyone has the opportunity to thrive and advance professionally. Explore this opportunity and be part of the next chapter in our history.

About the Mount Sinai Health System:

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 - discovering and applying new scientific learning and knowledge; developing safer, more effective treatments; educating the next generation of medical leaders and innovators; and supporting local communities by delivering high-quality care to all who need it. Through the integration of its hospitals, labs, and schools, Mount Sinai offers comprehensive health care solutions from birth through geriatrics, leveraging innovative approaches such as artificial intelligence and informatics while keeping patients' medical and emotional needs at the center of all treatment. The Health System includes more than 9,000 primary and specialty care physicians; 13 joint-venture outpatient surgery centers throughout the five boroughs of New York City, Westchester, Long Island, and Florida; and more than 30 affiliated community health centers. We are consistently ranked by U.S. News & World Report's Best Hospitals, receiving high "Honor Roll" status, and are highly ranked: No. 1 in Geriatrics, top 5 in Cardiology/Heart Surgery, and top 20 in Diabetes/Endocrinology, Gastroenterology/GI Surgery, Neurology/Neurosurgery, Orthopedics, Pulmonology/Lung Surgery, Rehabilitation, and Urology. New York Eye and Ear Infirmary of Mount Sinai is ranked No. 12 in Ophthalmology. U.S. News & World Report's "Best Children's Hospitals" ranks Mount Sinai Kravis Children's Hospital among the country's best in several pediatric specialties. The Icahn School of Medicine at Mount Sinai is ranked No. 11 nationwide in National Institutes of Health funding and in the 99th percentile in research dollars per investigator according to the Association of American Medical Colleges. Newsweek's "The World's Best Smart Hospitals" ranks The Mount Sinai Hospital as No. 1 in New York and in the top five globally, and Mount Sinai Morningside in the top 20 globally.

Equal Opportunity Employer

The Mount Sinai Health System is an equal opportunity employer, complying with all applicable federal civil rights laws. We do not discriminate, exclude, or treat individuals differently based on race, color, national origin, age, religion, disability, sex, sexual orientation, gender, veteran status, or any other characteristic protected by law. We are deeply committed to fostering an environment where all faculty, staff, students, trainees, patients, visitors, and the communities we serve feel respected and supported. Our goal is to create a healthcare and learning institution that actively works to remove barriers, address challenges, and promote fairness in all aspects of our organization.

• Masters degree or equivalent in  computational biology, bioinformatics, genomics, or a related field -  Ph.D. in a scientific domain preferred.

• Beginner level, with some experience in a scientific/academic computing environment or equivalent preferred.

• Strong programming skills in Python (required); familiarity with R strongly preferred - 
• Demonstrated experience working with single-cell genomics data - 
• Strong quantitative and statistical background - 
• Ability to work both independently and collaboratively in a highly iterative, interdisciplinary environment - 
• Interest in biological interpretation and hypothesis generation, not just data processing

• Masters degree or equivalent in  computational biology, bioinformatics, genomics, or a related field -  Ph.D. in a scientific domain preferred.

• Beginner level, with some experience in a scientific/academic computing environment or equivalent preferred.

• Strong programming skills in Python (required); familiarity with R strongly preferred - 
• Demonstrated experience working with single-cell genomics data - 
• Strong quantitative and statistical background - 
• Ability to work both independently and collaboratively in a highly iterative, interdisciplinary environment - 
• Interest in biological interpretation and hypothesis generation, not just data processing

Compensation Statement

The Mount Sinai Health System (MSHS) provides salary ranges that comply with the New York City Law on Salary Transparency in Job Advertisements. The salary range for the role is $72,473.00 - $108,709.00 Annually. Actual salaries depend on a variety of factors, including experience, education, and operational need. The salary range or contractual rate listed does not include bonuses/incentive, differential pay or other forms of compensation or benefits.

, 859 - Psychiatry - ISM, Icahn School of Medicine

Data Processing & Infrastructure

• Process raw sequencing data (FASTQ), including alignment and quantification for single-cell and single-nucleus assays 
• Perform genotype-based demultiplexing using tools such as cellsnp-lite and Vireo (or related methods) 
• Build and maintain reproducible, well-documented analysis pipelines 
• Genotype & VCF Handling (critical component)
• Generate, curate, and harmonize VCFs from whole-genome sequencing and SNP array data 
• Perform quality control, filtering, and format standardization across genotype sources 
• Implement and troubleshoot imputation workflows and integration of mixed genotype datasets 
• Ensure robust genotype-transcriptome linkage for accurate demultiplexing and downstream analyses

Single-Cell & Multiomic Analysis

• Analyze scRNA-seq, snATAC-seq, multiome, and spatial transcriptomics datasets using modern frameworks (e.g., Scanpy, SnapATAC2, Squidpy, Pegasus or related tools) 
• Perform dataset integration using probabilistic and deep learning approaches (e.g., scVI, scANVI or similar models) 
• Conduct differential expression and variance partitioning analyses across complex designs (donor, condition, batch) 
• Perform trajectory inference and lineage mapping across developmental systems 

Integrative & Translational Analysis

• Map organoid-derived cell states to in vivo fetal and postmortem datasets 
• Identify conserved transcriptional and regulatory programs across genetic and pharmacologic disease models 
• Infer gene regulatory networks and candidate signaling pathways 
• Collaborate closely with experimental scientists to design experiments and prioritize perturbation targets