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Single Cell Spatial Transcriptomics Jobs in Brooklyn, NY

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How much do single cell spatial transcriptomics jobs pay per hour?

As of Jul 19, 2026, the average hourly pay for single cell spatial transcriptomics in Brooklyn, NY is $22.76, according to ZipRecruiter salary data. Most workers in this role earn between $17.69 and $28.56 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Single Cell Spatial Transcriptomics Scientist, and why are they important?

To thrive as a Single Cell Spatial Transcriptomics Scientist, you need a strong background in molecular biology, genomics, and bioinformatics, typically supported by an advanced degree (PhD or MSc) in a relevant field. Familiarity with high-throughput sequencing platforms, spatial transcriptomics technologies (like 10x Genomics Visium or NanoString GeoMx), and data analysis tools such as R or Python is essential. Critical thinking, problem-solving, and effective communication are crucial soft skills for interpreting complex data and collaborating in multidisciplinary teams. These skills and qualities are vital for generating reliable insights into cellular function and spatial organization, which drive innovative research and discovery.

What are some typical challenges faced by professionals working in Single Cell Spatial Transcriptomics, and how can they be addressed?

Professionals in Single Cell Spatial Transcriptomics often encounter challenges related to handling large, complex data sets and integrating spatial information with single-cell transcriptomic profiles. These tasks demand strong computational skills and close collaboration with bioinformaticians and other researchers. Effective communication within interdisciplinary teams is essential to ensure experimental design aligns with downstream analysis needs. Staying updated with rapidly evolving technologies and best practices also helps professionals overcome technical hurdles and produce reliable, high-impact results.

What is single cell spatial transcriptomics?

Single cell spatial transcriptomics is a cutting-edge technique that allows researchers to analyze gene expression in individual cells while preserving their spatial location within a tissue. This method combines the high-resolution insights of single-cell RNA sequencing with spatial information, enabling scientists to understand how cells interact and organize within their native environments. It is widely used in biomedical research to study tissue architecture, disease mechanisms, and cellular heterogeneity.
What are popular job titles related to Single Cell Spatial Transcriptomics jobs in Brooklyn, NY? For Single Cell Spatial Transcriptomics jobs in Brooklyn, NY, the most frequently searched job titles are:
What job categories do people searching Single Cell Spatial Transcriptomics jobs in Brooklyn, NY look for? The top searched job categories for Single Cell Spatial Transcriptomics jobs in Brooklyn, NY are:
What cities near Brooklyn, NY are hiring for Single Cell Spatial Transcriptomics jobs? Cities near Brooklyn, NY with the most Single Cell Spatial Transcriptomics job openings:
Infographic showing various Single Cell Spatial Transcriptomics job openings in Brooklyn, NY as of July 2026, with employment types broken down into 100% Full Time. Highlights an 83% In-person, and 17% Remote job distribution, with an average salary of $47,340 per year, or $22.8 per hour.
Associate Scientist - Dr Sealfon's Lab (Computational Genomics & Large-Scale Molecular Data Analy...

Associate Scientist - Dr Sealfon's Lab (Computational Genomics & Large-Scale Molecular Data Analy...

Mount Sinai Health System

Manhattan, NY

$64K - $65K/yr

Full-time

Re-posted 24 days ago


Mount Sinai rating

7.8

Company rating: 7.8 out of 10

Based on 283 frontline employees who took The Breakroom Quiz

133rd of 886 rated healthcare providers


Job description

We are seeking a highly motivated Staff 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 Staff 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. The ideal candidate has deep expertise in single-cell transcriptomics and epigenomics, experience handling large-scale datasets, and strong quantitative and programming skills. Experience in machine learning and AI approaches is highly desirable.

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.

  • Ph.D. in Biological Science or related field
  • Three years experience

Preferred Skills

  • PhD in Computational Biology, Bioinformatics, Genomics, Statistics, Computer Science, or related field (or equivalent 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
  • Ph.D. in Biological Science or related field
  • Three years experience

Preferred Skills

  • PhD in Computational Biology, Bioinformatics, Genomics, Statistics, Computer Science, or related field (or equivalent 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

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 $58,661.00 - $98,978.78 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.

Non-Bargaining Unit, 841 - Neurology - ISM, Icahn School of Medicine

  • 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

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