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Computational Spatial Transcriptomics Jobs in Los Angeles, CA

Postdoctoral Fellow - Genomics Research

Duarte, CA · On-site

$51.40K - $69.80K/yr

... spatial transcriptomics, HiC/HiCHIP, RIBO-seq and next generation long reads sequencing from Oxford Nanopore. Participate in the development of new computational methods for downstream analysis of ...

... spatial transcriptomics, multiomics and related technologies. The successful applicant will: 1) ... computational biologists and bioinformaticians. * Willingness and ability to interface and work ...

Biomedical Technician

West Hollywood, CA · On-site

$28.50 - $37.75/hr

We actively collaborate with investigators to develop sophisticated or custom computational solutions for specific research questions, including advanced analysis for spatial transcriptomics data.

Computational Spatial Transcriptomics information

See Los Angeles, CA salary details

$44

$59

$79

How much do computational spatial transcriptomics jobs pay per hour?

As of May 28, 2026, the average hourly pay for computational spatial transcriptomics in Los Angeles, CA is $59.19, according to ZipRecruiter salary data. Most workers in this role earn between $50.53 and $79.28 per hour, depending on experience, location, and employer.

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 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 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 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 are popular job titles related to Computational Spatial Transcriptomics jobs in Los Angeles, CA? For Computational Spatial Transcriptomics jobs in Los Angeles, CA, the most frequently searched job titles are:
What job categories do people searching Computational Spatial Transcriptomics jobs in Los Angeles, CA look for? The top searched job categories for Computational Spatial Transcriptomics jobs in Los Angeles, CA are:
What cities near Los Angeles, CA are hiring for Computational Spatial Transcriptomics jobs? Cities near Los Angeles, CA with the most Computational Spatial Transcriptomics job openings:

Genomics Biomedical Technician

Cedars Sinai

West Hollywood, CA • On-site

$28.50 - $37.75/hr

Other

Posted 4 days ago


Job description

The Applied Genomics, Computation & Translational Core is looking for a Biomedical Technician to join the team! 

Candidates with experience in single-cell and spatial assay technologies are highly desirable. This includes familiarity with techniques such as single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, multiplex imaging, and other high-dimensional molecular profiling platforms. A working knowledge of sample preparation workflows, library preparation, quality control metrics, and data generation associated with next-generation sequencing or imaging-based assays is strongly valued. Experience handling complex biological specimens and maintaining rigorous data integrity within high-throughput experimental environments is also preferred.

The Cedars-Sinai Applied Genomics, Computation & Translational (AGCT) Core is an automated, high-throughput genomics facility equipped with the latest next-generation sequencing technologies. We specialize in single-cell and spatial omics, utilizing platforms including 10x Genomics (Chromium X, Xenium Analyzer, Visium CytAssist), Parse Biosciences, Scale Biosciences, Illumina, Singular Genomics G4X , and Bruker CosMX SMI. We also offer expertise in long-read sequencing via Oxford Nanopore Technologies (PromethION 24, MinION) and high-throughput short-read sequencing on the Illumina NovaSeq X Plus. We provide comprehensive support covering sample preparation, library construction, and diverse sequencing applications including bulk cell RNA-Seq, WGS/WES, ATAC-Seq, and metagenomics. 

The AGCT Core also delivers extensive bioinformatics analysis. Standard pipelines are established for primary data processing across all services, encompassing read alignment, quality control, expression quantification, variant calling, and peak calling. We also provide downstream analysis packages to help analyze these data in the context of the researcher's experimental design. We actively collaborate with investigators to develop sophisticated or custom computational solutions for specific research questions, including advanced analysis for spatial transcriptomics data. Our bioinformatics support extends to results interpretation, generation of publication-ready figures, and drafting manuscript methodology. 

To learn more please visit Applied Genomics, Computation & Translational Core | Cedars-Sinai. 

Are you ready to be a part of breakthrough research? 

The AGCT Core Biomedical Technician contributes to the laboratory sciences team of the lab. They work independently as part of a team under direct supervision of a team lead.  The Biomedical Technician is responsible for performing laboratory benchwork strictly according to Standard Operating Procedures with accurate documentation and a theoretical understanding of assays utilized.  They perform quality control on RNA and DNA samples, understanding the nuances of sample quality and qualifications.  The Biomedical Technician contributes to the success of projects by providing good oral and written communication, documentation, and attentiveness to detail. They work with state-of-the-art technologies and instruments, performing next generation sequencing library preparation and sequencing.

Primary Duties and Responsibilities

  • Performs a variety of project-specific process development tasks for multiple clients following standard operating procedures (SOPs).
  • Maintains good documentation in laboratory notebooks, data record/transfer, SOPs, and batch records.
  • Drafts standard operating procedures and maintains computer database.
  • Verifies samples received, logs samples into systems, and may transport to appropriate environment within the facility for storage following SOPs.
  • Performs lab maintenance duties, including glassware cleaning and sterilization.
  • Maintains lab equipment and related records.
  • Prepares cGMP production room, maintains material inventories, and places orders for equipment and supplies.
  • Assists in the operation of specialized equipment and machinery.
  • Ensures all activities comply with regulatory guidelines and safety standards, as appropriate.

Department Specific Responsibilities

  • Construction of next generation sequencing libraries for bulk cell, single cell, and/or spatial omics using commercially available reagent kits.
  • Illumina short-read sequencing and/or Oxford Nanopore Technologies long-read sequencing of NGS libraries.
  • DNA/RNA QC via fluorescent quantification and automated electrophoresis.
  • Operation of state-of-the-art genomics equipment including NGS sequencers, automated liquid handlers, and tissue imagers, as well as standard laboratory equipment such as thermal cyclers, centrifuges, and qPCR machines.
  • Mathematical calculations, including fold dilution, normalization, and conversions.
  • Understand, analyze, and interpret DNA/RNA/NGS library/sequencing QC results. 
  • Liaise with post-doctoral, doctoral, and staff researchers, clinical investigators, and principal investigators to provide quality customer service.
  • Handle multiple demands and/or manage complex and competing priorities, pivoting as needed based on current needs in a dynamic environment.
  • Apply advanced knowledge of science/learning/specialized intellectual instructions to analyze, interpret, or make deductions from varying facts or circumstances.
  • Provide and/or support a level of work excellence and accuracy; recognize and address flaws or errors that others may overlook.
  • Regular oral and written communication with team members and team lead.
  • Accurate and detailed electronic documentation of work performed and results obtained.
  • Work independently as part of a team under direct supervision of a team lead.
  • Observe and comply with all safety standards and procedures.

Required Qualifications

  • Associate Degree or College Diploma in Biology, Biochemistry, or a related scientific or engineering discipline.
  • Minimum of one (1) year of hands-on experience in a laboratory or biotechnology environment.
  • Demonstrated experience working with biomedical equipment, including routine maintenance, calibration, troubleshooting, and/or performance testing.

Strongly Preferred

  • Experience with single-cell and spatial assay technologies. This includes familiarity with techniques such as single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, multiplex imaging, or other high-dimensional molecular profiling platforms.
  • Working knowledge of sample preparation workflows, library preparation, quality control metrics, and data generation associated with next-generation sequencing or imaging-based assays.
  • Experience handling complex biological specimens and maintaining data integrity in high-throughput experimental environments.
  • Bachelor's Degree in Biology, Biochemistry, or a related science or engineering field.