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Computational Spatial Transcriptomics Jobs in Secaucus, NJ

Post Doctorate Associate

New York, NY · On-site

$62K - $70K/yr

In addition, candidates will contribute to the analysis of single-cell and spatial transcriptomics datasets, including MERFISH and spatial proteomics. Familiarity with computational pipelines for ...

RESEARCH SCHOLAR

New York, NY · On-site

$48K - $50K/yr

... spatial transcriptomics experiments, including MERFISH, immunofluorescence, spatial proteomics, and live-cell imaging. * Analyze and integrate single-cell datasets using established computational ...

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Computational Spatial Transcriptomics information

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How much do computational spatial transcriptomics jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for computational spatial transcriptomics in Secaucus, NJ is $55.84, according to ZipRecruiter salary data. Most workers in this role earn between $47.64 and $74.81 per hour, depending on experience, location, and employer.

What are some typical challenges faced when working in computational spatial transcriptomics, and how can new team members prepare for them?

Professionals in computational spatial transcriptomics often encounter challenges related to handling and analyzing large, complex datasets that combine spatial and gene expression information. Integrating data from different technologies and ensuring data quality can be demanding, requiring strong programming skills and familiarity with bioinformatics pipelines. New team members can prepare by strengthening their skills in statistical analysis, programming languages like Python or R, and staying updated on the latest spatial transcriptomics techniques. Collaborating closely with experimental biologists and data scientists is also key to overcoming these challenges and driving successful research outcomes.

What is the difference between Computational Spatial Transcriptomics vs Computational Biologist?

AspectComputational Spatial TranscriptomicsComputational Biologist
Required CredentialsAdvanced degrees in bioinformatics, computational biology, or related fields; experience with spatial data analysisTypically a PhD or Master's in biology, bioinformatics, or related disciplines; strong programming skills
Work EnvironmentResearch labs, biotech companies, academic institutions focusing on spatial genomicsResearch institutions, biotech firms, academia working on biological data analysis
Industry UsageSpecialized in spatial transcriptomics techniques and data interpretationBroad biological data analysis across various fields

Computational Spatial Transcriptomics focuses on analyzing spatial gene expression data within tissues, requiring specialized skills in spatial data processing. In contrast, Computational Biologists work on a wider range of biological data types. While both roles involve bioinformatics expertise, the former emphasizes spatial data analysis techniques specific to transcriptomics.

What is computational spatial transcriptomics?

Computational spatial transcriptomics is a field that combines advanced computational methods with spatial transcriptomics, a technique that measures gene expression within the physical context of tissue samples. It involves processing and analyzing large datasets to map where specific genes are active within tissues, helping researchers understand how cells interact and function in their native environments. This approach is crucial for studies in developmental biology, cancer research, and neuroscience, as it provides insights into cellular organization and tissue architecture. Computational tools help extract meaningful patterns from complex data, enabling discoveries that were previously impossible with traditional methods.

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

To excel in Computational Spatial Transcriptomics, you need a strong background in bioinformatics, genomics, and statistical data analysis, typically supported by advanced degrees in computational biology or related fields. Familiarity with programming languages (such as R and Python), spatial transcriptomics platforms (like 10x Genomics Visium), and high-throughput sequencing data analysis tools is essential. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for interpreting complex datasets and collaborating with multidisciplinary teams. These competencies ensure accurate data interpretation, innovative research, and successful integration of spatial transcriptomics insights into biological and clinical applications.
What job categories do people searching Computational Spatial Transcriptomics jobs in Secaucus, NJ look for? The top searched job categories for Computational Spatial Transcriptomics jobs in Secaucus, NJ are:
What cities near Secaucus, NJ are hiring for Computational Spatial Transcriptomics jobs? Cities near Secaucus, NJ with the most Computational Spatial Transcriptomics job openings:
Associate Computational Scientist-Psychiatry Dr. Kaji

Associate Computational Scientist-Psychiatry Dr. Kaji

Mount Sinai Hospital

Manhattan, NY • On-site

Full-time

Re-posted 12 days ago


Mount Sinai rating

7.8

Company rating: 7.8 out of 10

Based on 283 frontline employees who took The Breakroom Quiz

131st of 884 rated healthcare providers


Job description


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
Responsibilities
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

Qualifications
  • 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

About Us
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.

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