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Single Cell Spatial Transcriptomics Jobs in Ramsey, MN

Single Cell Spatial Transcriptomics information

See Ramsey, MN salary details

$13

$22

$31

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

As of Jun 9, 2026, the average hourly pay for single cell spatial transcriptomics in Ramsey, MN is $22.47, according to ZipRecruiter salary data. Most workers in this role earn between $17.45 and $28.22 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.
Infographic showing various Single Cell Spatial Transcriptomics job openings in Ramsey, MN as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $46,745 per year, or $22.5 per hour.
Post-Doctoral Associate - Bioinformatics & Computational Biology

Post-Doctoral Associate - Bioinformatics & Computational Biology

University of Minnesota

Minneapolis, MN

$62K - $75K/yr

Full-time

Medical, Dental, Life

Posted 5 days ago


Job description

About the Job
 

Required Qualifications:
A PhD degree in related field (Bioinformatics, Computer Science, Statistics, etc.) obtained in the last 1~2 years.
Strong quantitative data analysis background (machine learning, biostatistics, etc.) and/or computational genomics/genetics experiences (spatial transcriptomics, single-cell sequencing, high-throughput omics sequencing data analysis, TWAS/GWAS, etc.) or other relevant areas.
Strong programming skills: (e.g., R, Python, and Unix Shell).
Quick learning capability for new technologies and analytical methods
Strong communication and interpersonal skills and a track record of collaborative work in multidisciplinary research environment.
Job description:
Zhus lab is a dry lab. The research interests are mainly focused on the novel computational methodology design and integrative multi-modality data analysis to (1) enhance the spatial profiling technology and (2) screen the pathogenic upstream regulator.
Responsibilities:
Develop novel computational methods to enhance the power of spatial-omics technology.
Develop novel computational methods to advance understanding of the complex genetic diseases, e.g., fatty liver disease, diabetes, etc.
Conduct rigorous and reproducible integrative multi-modality data analysis (generated from spatially resolved sequencing, single-cell sequencing, long-read and short-read bulk sequencing, etc.) to shed lights on the coordinated biological regulatory mechanism from different omics layers.
Publish high-impact factor papers and give presentations of novel research findings in academic journals and conferences.
Manage and maintain software/database for long-standing user support.

Pay and Benefits
 

Pay Range: $62,232 - 75,564 (follows NIH stipend levels); depending on education/qualifications/experience

Please visit the Benefits for Postdoctoral Candidates website for more information regarding benefit eligibility.

  • Competitive wages, paid holidays, and generous time off
  • Continuous learning opportunities through professional training
  • Medical, dental, and pharmacy plans
  • Healthcare and dependent care flexible spending accounts
  • University HSA contributions
  • Disability and life insurance
  • Employee wellbeing program
  • Financial counseling services
  • Employee Assistance Program with eight sessions of counseling at no cost
How To Apply
 

Applications must be submitted online.  To be considered for this position, please click the Apply button and follow the instructions.  You will be given the opportunity to complete an online application for the position and attach (all three required) -

  • cover letter
  • CV
  • the name and contact information for three professional references

Additional documents may be attached after application by accessing your "My Job Applications" page and uploading documents in the "My Cover Letters and Attachments" section.

To request an accommodation during the application process, please e-mail employ@umn.edu or call (612) 624-UOHR (8647).

Diversity
 

The University recognizes and values the importance of diversity and inclusion in enriching the employment experience of its employees and in supporting the academic mission.  The University is committed to attracting and retaining employees with varying identities and backgrounds.

The University of Minnesota provides equal access to and opportunity in its programs, facilities, and employment without regard to race, color, creed, religion, national origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression.  To learn more about diversity at the U:  http://diversity.umn.edu

Employment Requirements
 

Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective employees are eligible to work here. Criminal convictions do not automatically disqualify finalists from employment.

About University of Minnesota
 

The University of Minnesota, Twin Cities (UMTC)

The University of Minnesota, Twin Cities (UMTC), is among the largest public research universities in the country, offering undergraduate, graduate, and professional students a multitude of opportunities for study and research. Located at the heart of one of the nation's most vibrant, diverse metropolitan communities, students on the campuses in Minneapolis and St. Paul benefit from extensive partnerships with world-renowned health centers, international corporations, government agencies, and arts, nonprofit, and public service organizations.

At the University of Minnesota, we are proud to be recognized by the Star Tribune as a Top Workplace for 2021, as well as by Forbes as Best Employers for Women and one of Americas Best Employers (2015, 2018, 2019, 2023), Best Employer for Diversity (2019, 2020), Best Employer for New Grads (2018, 2019), and Best Employer by State (2019, 2022).